ABSTRACT
This publisher's note contains corrections to Appl. Opt.61, 3924 (2022)APOPAI0003-693510.1364/AO.454357.
ABSTRACT
Titanocene dichloride and budotitane have opened a new chapter in medicinal chemistry of titanium(IV) complexes being novel non-platinum antitumor metallic agents. Numerous efforts have led to the discovery of the diamino bis-phenolato titanium(IV) complexes. Among which, the [ONNO] and [ONON] type ligands namely Salan, Salen and Salalen coordinated titanium(IV) alkoxyl complexes have demonstrated significantly enhanced aqueous stability, their in vitro and in vivo antitumor efficacy, mechanism of action, structure-activity relationships and combined tumor therapy have been intensively investigated. Replacement of the labile alkoxyls with a second chelator resulted in structural rigid titanium(IV) complexes, which showed exceedingly good aqueous stability and potent antitumor activity both in vitro and in vivo. The unique ligand system successfully allowed the access of isotopic [45Ti]Titanium(IV) complexes, post-synthetic modification, facile synthetic protocols and antitumor congeneric zirconium(IV) and hafnium(IV) complexes. This review presents recent research progress in the field of antitumor group 4 metal complexes stabilized with phenolato ligands; especially their structure-activity relationships are summarized.
Subject(s)
Antineoplastic Agents , Coordination Complexes , Neoplasms , Organometallic Compounds , Humans , Titanium/pharmacology , Titanium/chemistry , Titanium/therapeutic use , Ligands , Neoplasms/drug therapy , Organometallic Compounds/chemistry , Organometallic Compounds/pharmacology , Organometallic Compounds/therapeutic use , Structure-Activity Relationship , Antineoplastic Agents/chemistry , Coordination Complexes/pharmacologyABSTRACT
The miniaturization of nodes poses new challenges in semiconductor manufacturing. Optical proximity correction (OPC) is typically performed to satisfy technical requirements through iterative optimization. However, this method is expensive and slow. This study proposes a framework based on patch loss and a generative adversarial network through unsupervised learning to address these problems. The target pattern is used as the input of the model to avoid dependence on OPC tools. Thus, a fast approach is proposed for realizing OPC swiftly.
