An efficient cell micronucleus classification network based on multi-layer perception attention mechanism.

Cellular micronucleus detection plays an important role in pathological toxicology detection and early cancer diagnosis. To address the challenges of tiny targets, high inter-class similarity, limited sample data and class imbalance in the field of cellular micronucleus image detection, this paper proposes a lightweight network called MobileViT-MN (Micronucleus), which integrates a multilayer perceptual attention mechanism. Considering that limited data and class imbalance may lead to overfitting of the model, we employ data augmentation to mitigate this problem.

The valence state of iron-based nanomaterials determines the ferroptosis potential in a zebrafish model.

Many nanomaterials containing different valences of iron have been designed for applications in biomedicine, energy, catalyzers, nanoenzymes, and so on. However, the toxic effects of the valence state of iron in iron-based nanomaterials are still unclear. Here, three different-valence iron-based nanomaterials (nFe@FeO, nFeO and nFeO) were synthesized and exposed to zebrafish embryos and mammalian cardiomyocytes.