Publications by authors named "T Naumann"

Plant roots grow in association with a community of microorganisms collectively known as the rhizosphere microbiome. Immune activation in response to elicitors like the flagellin-derived epitope flg22 restricts bacteria on plant roots but also inhibits plant growth. Some commensal root-associated bacteria are capable of suppressing the plant immune response to elicitors.

View Article and Find Full Text PDF
Article Synopsis
  • Biomedical image analysis is crucial for biomedical research, and traditional methods treat tasks like segmentation, detection, and recognition separately.
  • BiomedParse is introduced as a foundation model that can handle these tasks simultaneously across nine imaging modalities, enhancing accuracy and enabling new applications like object segmentation based on textual descriptions.
  • The model was trained on a vast dataset of over 6 million image-text pairs, demonstrating superior performance in image segmentation, especially for irregularly shaped objects, making it a comprehensive tool for biomedical image analysis.
View Article and Find Full Text PDF
Article Synopsis
  • Using artificial intelligence (AI) in healthcare can help doctors make better decisions but has challenges like ensuring it’s safe and fair.
  • The paper suggests making clear rules and methods to develop and test AI systems for patient safety.
  • A big meeting with over 200 experts took place to find solutions on using AI in healthcare, leading to important recommendations for better AI systems.
View Article and Find Full Text PDF

Although several porous carbon/graphene nanoribbons (GNRs) have been prepared, a direct comparison of the electronic properties between a nonporous GNR and its periodically perforated counterpart is still missing. Here, we report the synthesis of porous 12-atom-wide armchair-edged GNRs from a bromoarene precursor on a Au(111) surface via hierarchical Ullmann and dehydrogenative coupling. The selective formation of porous 12-GNRs was achieved through thermodynamic and kinetic reaction control combined with tailored precursor design.

View Article and Find Full Text PDF

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.

View Article and Find Full Text PDF