Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.

Self-supervised learning (SSL) has gained attention in the medical field as a deep learning approach utilizing unlabeled data. The Jigsaw puzzle task in SSL enables models to learn both features of images and the positional relationships within images. In breast cancer diagnosis, radiologists evaluate not only lesion-specific features but also the surrounding breast structures.

Bis(acetylacetonato)bis(pyrazolato)ruthenate(iii) as a redox-active scorpionate ligand.

The potential of a new anionic octahedral metal complex [Ru(III)(acac)2(pz)2](-) ((-)) (pzH = pyrazole) as a ligand with a scorpionate coordination behaviour like tris(pyrazolyl)borate (tp) and reversible redox activity is presented. Trinuclear metal complexes, [Ru(III)2Zn(II)(acac)4(pz)4] () and [Ru(II)Ru(III)2(acac)4(pz)4] (), were each synthesized by the reaction of ZnCl2 or Ru3(CO)12 with [Ru(III)(acac)2(pz)(pzH)] (H) that is in situ deprotonated and acts as a precursor of (-). Single-crystal X-ray diffraction studies clarified that (-) acts as a scorpionate ligand; two (-) units in and one unit in function as bidentate ligands with two pyrazolates as pincers, while another (-) unit in functions as a tridentate ligand with one oxygen atom as a tail in addition to the two pyrazolate pincers.