As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fill existing data gaps by employing two machine learning models, eXtreme Gradient Boosting and HistGradientBoosting algorithms to produce precise country-level predictions of nitrogen (N), phosphorus pentoxide (PO), and potassium oxide (KO) application rates. Subsequently, we created a comprehensive dataset of 5-arcmin resolution maps depicting the application rates of each fertilizer for 13 major crop groups from 1961 to 2019.
View Article and Find Full Text PDFGenetic engineering of regulatory T cells (Tregs) presents a promising avenue for advancing immunotherapeutic strategies, particularly in autoimmune diseases and transplantation. This study explores the modification of Tregs via mRNA electroporation, investigating the influence of T-cell activation status on transfection efficiency, phenotype, and functionality. For this CD45RA Tregs were isolated, expanded, and modified to overexpress brain-derived neurotrophic factor (BDNF).
View Article and Find Full Text PDFClimate change has altered the timing of recurring biological cycles in both plants and animals. Phenological changes may be unequal within and among trophic levels, potentially impacting the intricate interactions that regulate ecosystem functioning. Here we compile and analyse a global dataset of terrestrial phenological observations, including nearly half a million time series for both plants and animals.
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