Primary tissues are fixed by the magnetic microneedle scaffold and cut into small pieces by a slicing device, which are imparted with magnetic responsiveness because of the encapsulated microneedle ...

The free Metalosate T.E.A.M. platform translates complex data into clear, actionable recommendations for specialty crop ...

The Genotype-Tissue Expression (GTEx) project provides a valuable resource for investigating gene regulation across various human tissues. However, its cross-sectional design introduces technical ...

Researchers at the University of Jyväskylä, in collaboration with the University of Turku's Institute of Biomedicine, University of Helsinki and Nova Hospital of Central Finland, have developed an ...

Researchers at the University of Michigan and Brown University have developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the ...

A liver cancer diagnosis frequently leads to surgery, with the goal of completely removing all malignant tissue. To ensure ...

A team of scientists has developed a new AI software tool called 'BANKSY' that automatically recognizes the cell types present in a tissue, such as muscle cells, nerve cells and fat cells. Going a ...

Micro- and nanoplastic particles concentrate at far higher levels in brain tissue adjacent to tumors than in healthy brain ...

Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.