In this study, we determined the contribution of juvenile neurogenesis to the performance of mice on a remote memory for temporally based association task and in a novelty based spatial pattern separation task. This was accomplished by mating homozygous DNMT1-loxP mice with heterozygous GFAP-Cre mice and comparing Cre+ (no postnatal neurogenesis) to Cre- (wild type) littermate offspring. The results indicate that Cre+ mice are impaired relative to Cre- mice in the remote memory for a temporal based association task and in a novelty based spatial pattern separation task. These results support the temporal integration model of Aimone et al., [(2006) Nat Neurosci 9:723-727] and provide further support for an important role for postnatally born neurons in spatial pattern separation. In contrast, Cre+ mice are not impaired relative to Cre- mice in an object-context recognition task and a spatial location recognition task. These latter data suggest that postnatally derived neurons in the dentate gyrus (DG) do not support all spatial and object recognition functions of the DG.

Biomimetic surface coatings based on plant polyphenols and catecholamines have been used broadly in a variety of applications. However, the lack of a rational cost-effective platform for screening these coatings and their properties limits the true potential of these functional materials to be unleashed. Here, we investigated the oxidation behavior and coating formation ability of a library consisting of 45 phenolic compounds and catecholamines. UV-vis spectroscopy demonstrated significant acceleration of oxidation and polymerization under UV irradiation. We discovered that several binary mixtures resulted in non-additive behavior (synergistic or antagonistic effect) yielding much thicker or thinner coatings than individual compounds measured by ellipsometry. To investigate the properties of coatings derived from new combinations, we used a miniaturized high-throughput strategy to screen 2,532 spots coated with single, binary, and ternary combinations of coating precursors in one run. We evaluated the use of machine learning models to learn the relation between the chemical structure of the precursors and the thickness of the nanocoatings. Formation and stability of nanocoatings were investigated in a high-throughput manner via discontinuous dewetting. 30 stable combinations (hits) were used to tune the surface wettability and to form water droplet microarray and spot size gradients of water droplets on the coated surface. No toxicity was observed against eukaryotic HeLa cells and Pseudomonas aeruginosa (strain PA30) bacteria after 24 h incubation at 37 °C. The strategy introduced here for high-throughput screening of nanocoatings derived from combinations of coating precursors enables the discovery of new functional materials for various applications in science and technology in a cost-effective miniaturized manner.