Metal-organic frameworks (MOFs) are promising platforms for the synthesis of nanoparticles for diverse medical applications. Their fundamental design principles allow for significant control of the framework architecture and pore chemistry, enabling directed functionalization for nanomedical applications. However, before applying novel nanomaterials to patients, it is imperative to understand their potential health risks. In this study, the nanosafety of different MOF nanoparticles is analyzed comprehensively for diverse medical applications. The authors first evaluate the effects of MOFs on human endothelial and mouse lung cells, which constitute a first line of defense upon systemic blood-mediated and local lung-specific applications of nanoparticles. Second, we validated these MOFs for multifunctional surface coatings of dental implants using human gingiva fibroblasts. Moreover, biocompatibility of MOFs is assessed for surface coating of nerve guidance tubes using human Schwann cells and rat dorsal root ganglion cultures. The main finding of this study is that the nanosafety and principal suitability of our MOF nanoparticles as novel agents for drug delivery and implant coatings strongly varies with the effector cell type. We conclude that it is therefore necessary to carefully evaluate the nanosafety of MOF nanomaterials with respect to their particular medical application and their interacting primary cell types, respectively.

Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents (Np), but little is known about how Np affects genomic selection (GS) in RS, especially the persistency of prediction accuracy (rg,g^) and genetic gain. Synthetics were simulated by intermating Np= 2–32 parent lines from an ancestral population with short- or long-range linkage disequilibrium (LDA) and subjected to multiple cycles of GS. We determined rg,g^ and genetic gain across 30 cycles for different training set (TS) sizes, marker densities, and generations of recombination before model training. Contributions to rg,g^ and genetic gain from pedigree relationships, as well as from cosegregation and LDA between QTL and markers, were analyzed via four scenarios differing in (i) the relatedness between TS and selection candidates and (ii) whether selection was based on markers or pedigree records. Persistency of rg,g^ was high for small Np, where predominantly cosegregation contributed to rg,g^, but also for large Np, where LDA replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing Np > 4, given long-range LDA in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to rg,g^ for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size (NTS) and higher marker density improved persistency of rg,g^ and hence genetic gain, but additional recombinations could not increase genetic gain.

Genomic selection (GS) offers the possibility to estimate the effects of genome-wide molecular markers, which can be used to calculate genomic estimated breeding values (GEBVs) for individuals without phenotypes. GEBVs can serve as a selection criterion in recurrent GS, maximizing single-cycle but not necessarily long-term genetic gain. As simple genome-wide sums, GEBVs do not take into account other genomic information, such as the map positions of loci and linkage phases of alleles. Therefore, we herein propose a novel selection criterion called expected maximum haploid breeding value (EMBV). EMBV predicts the expected performance of the best among a limited number of gametes that a candidate contributes to the next generation, if selected. We used simulations to examine the performance of EMBV in comparison with GEBV as well as the recently proposed criterion optimal haploid value (OHV) and weighted GS. We considered different population sizes, numbers of selected candidates, chromosome numbers and levels of dominant gene action. Criterion EMBV outperformed GEBV after about 5 selection cycles, achieved higher long-term genetic gain and maintained higher diversity in the population. The other selection criteria showed the potential to surpass both GEBV and EMBV in advanced cycles of the breeding program, but yielded substantially lower genetic gain in early to intermediate cycles, which makes them unattractive for practical breeding. Moreover, they were largely inferior in scenarios with dominant gene action. Overall, EMBV shows high potential to be a promising alternative selection criterion to GEBV for recurrent genomic selection.

Overexpression of Hairless (H) causes a remarkable degree of tissue loss and apoptosis during imaginal development. H functions as antagonist in the Notch-signaling pathway in Drosophila, and the link to growth and apoptosis is poorly understood. To further our insight into H-mediated apoptosis, we performed two large-scale screens for modifiers of a small rough eye phenotype caused by H overexpression. Both loss-and gain-of-function screens revealed known and new genetic interactors representing diverse cellular functions. Many of them did not cause eye phenotypes on their own, emphasizing a specific genetic interaction with H. As expected, we also identified components of different signaling pathways supposed to be involved in the regulation of cell growth and cell death. Accordingly, some of them also acted as modifiers of proapoptotic genes, suggesting a more general involvement in the regulation of apoptosis. Overall, these screens highlight the importance of H and the Notch pathway in mediating cell death in response to developmental and environmental cues and emphasize their role in maintaining developmental cellular homeostasis.

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