Nonaromatic Organonickel(II) Phototheranostics.

Earth-abundant metal-based theranostics, agents that integrate diagnostic and therapeutic functions within the same molecule, may hold the key to the development of low-cost personalized medicines. Here, we report a set of O-linked nonaromatic benzitripyrrin (C^N^N^N) macrocyclic organonickel(II) complexes, Ni-1-4, containing strong σ-donating M-C bonds. Complexes Ni-1-4 are characterized by a square-planar coordination geometry as inferred from the structural studies of Ni-1. They integrate photothermal therapy, photothermal imaging, and photoacoustic imaging (PAI) within one system. This makes them attractive as potential phototheranostics. Relative to traditional Ni(II) porphyrins, such as F20TPP (tetrapentafluorophenylporphyrin), the lowest energy absorption of Ni-1 is shifted into the near infrared region, presumably as a consequence of Ni-C bonding. Ultrafast transient absorption spectroscopy combined with theoretical calculations revealed that, upon photoexcitation, a higher population of ligand-centered and 3MLCT states is seen in Ni-1 relative to NiTPBP (TPBP = 6,11,16,21-tetraphenylbenziporphyrin). Encapsulating Ni-1 in 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE-PEG2000) afforded nanoparticles, Ni-1@DSPE, displaying red-shifted absorption features, as well as good photothermal conversion efficiency (∼45%) in aqueous media. Proof-of-principle experiments involving thrombus treatment were carried out both in vitro and in vivo. It was found that Ni-1@DSPE in combination with 785 nm photo-irradiation for 3 min (0.3 W/cm2) proved successful in removing blood clots from a mouse thrombus model as monitored by photoacoustic imaging (PAI). The present work highlights the promise of organonickel(II) complexes as potential theranostics and the benefits that can accrue from manipulating the excited-state features of early transition-metal complexes via, for example, interrupting π-conjugation pathways.

Unusual near infrared (NIR) fluorescent palladium(ii) macrocyclic complexes containing M-C bonds with bioimaging capability.

Near infrared (NIR) luminescent metal complexes are promising probes in bioimaging and biosensing, however they generally suffer from oxygen interference arising from heavy metal effects. We designed new tetradentate macrocyclic benzitripyrrin (C^N^N^N) ligands by combination of M-C bond formation and reducing the π-conjugation to achieve NIR fluorescent Pd complexes (700-1000 nm) with quantum yields up to 14%. To understand the origin of NIR fluorescence, detailed analyses by density functional theory/time-dependent density functional theory (DFT/TDDFT) calculations together with femtosecond and nanosecond transient absorption spectroscopies suggest that M-C bond formation indeed leads to destabilization of the d-d excited state and less effective quenching of emission; and importantly, small spin-orbital coupling (SOC) and the large singlet-triplet energy gap are the primary causes of the non-population of triplet states. Comparison of PdII and PtII analogues shows that the non-radiative channel of the out-plane vibration of the tripyrrin plane effectively quenches the fluorescence of the PtII complex but not the PdII congener. We also demonstrate the proof-of-concept applications of PdII complexes (Pd-1 and Pd-3) encapsulated in silica nanoparticles, in both in vitro and in vivo bioimaging experiments without oxygen interference. Moreover, pH-induced reversible switching of NIR fluorescence was achieved even intracellularly using the Pd complex (Pd-2), which shows the potential to further develop perspective stimuli-responsive NIR materials.

An ART-based construction of RBF networks.

Radial basis function (RBF) networks are widely used for modeling a function from given input-output patterns. However, two difficulties are involved with traditional RBF (TRBF) networks: The initial configuration of an RBF network needs to be determined by a trial-and-error method, and the performance suffers when the desired output has abrupt changes or constant values in certain intervals. We propose a novel approach to over. come these difficulties. New kernel functions are used for hidden nodes, and the number of nodes is determined automatically by an adaptive resonance theory (ART)-like algorithm. Parameters and weights are initialized appropriately, and then tuned and adjusted by the gradient-descent method to improve the performance of the network. Experimental results have shown that the RBF networks constructed by our method have a smaller number of nodes, a faster learning speed, and a smaller approximation error than the networks produced by other methods.