Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

Case_Study_4_weed_management_evaluation_Raw_Image_Data_1_of_10

Part 1 of 10 of raw individual images with gps log and ground truth. GPS log and ground truth are in part 10

Case_Study_4_weed_management_evaluation_Raw_Image_Data_10_of_10_GroundTruth

Part 10 of 10 of raw individual images with gps log and ground truth

Case_Study_4_weed_management_evaluation_Raw_Image_Data_2_of_10

Part 2 of 10 of raw individual images with gps log and ground truth. GPS log and ground truth are in part 10

Stromal Cells Derived from Visceral and Obese Adipose Tissue Promote Growth of Ovarian Cancers

<div><p>Obesity, and in particular visceral obesity, has been associated with an increased risk of developing cancers as well as higher rates of mortality following diagnosis. The impact of obesity on adipose-derived stromal cells (ASC), which contribute to the formation of tumor stroma, is unknown. Here we hypothesized that visceral source and diet-induced obesity (DIO) changes the ASC phenotype, contributing to the tumor promoting effects of obesity. We found that ASC isolated from subcutaneous (SC-ASC) and visceral (V-ASC) white adipose tissue(WAT) of lean(Le) and obese(Ob) mice exhibited similar mesenchymal cell surface markers expression, and had comparable effects on ovarian cancer cell proliferation and migration. Obese and visceral derived ASC proliferated slower and exhibited impaired differentiation into adipocytes and osteocytes <i>in vitro</i> as compared to ASC derived from subcutaneous WAT of lean mice. Intraperitoneal co-injection of ovarian cancer cells with obese or visceral derived ASC, but not lean SC-ASC, increased growth of intraperitoneal ID8 tumors as compared to controls. Obese and V-ASC increased stromal infiltration of inflammatory cells, including CD3+ T cells and F4/80+ macrophages. Obese and visceral derived ASC, but not lean SC-ASC, increased expression of chemotactic factors IL-6, MIP-2, and MCP-1 when cultured with tumor cells. Overall, these results demonstrate that obese and V-ASC have a unique phenotype, with more limited proliferation and differentiation capacity but enhanced expression of chemotactic factors in response to malignant cells which support infiltration of inflammatory cells and support tumor growth and dissemination.</p></div