Maternal high-protein diet modulates hepatic growth axis in weaning piglets by reprogramming the IGFBP-3 gene.

PURPOSE: The aim of this study was to investigate the effects of maternal high dietary protein intake on the hepatic growth axis in offspring. METHODS: Fourteen primiparous purebred Meishan sows were fed either a standard-protein (SP, n = 7) diet or a high-protein (HP, 150% of SP, n = 7) diet during pregnancy. Offspring (one male and one female per group, n = 14) on day 70 of the embryonic stage and on days 1, 35 and 180 after birth were selected, weighed and killed. Serum samples were analyzed for Tch, insulin and insulin-like growth factor-binding protein 3 (IGFBP-3) levels. Liver samples were analyzed for IGFBP-3 and IGF-I mRNA expression by qRT-PCR and for IGFBP-3, IGF1R and growth hormone receptor (GHR) protein expression by Western blotting. The underlying mechanism of IGFBP-3 regulation was determined by methylated DNA immunoprecipitation (MeDIP) and chromatin immunoprecipitation (ChIP). RESULTS: High-protein exposure resulted in significantly higher body and liver weights of piglets, and it increased their serum T3 and T4 levels at birth and/or at weaning. Furthermore, the IGFBP-3 protein content in the liver and serum was significantly reduced in the HP-exposed weaning piglets, whereas at the transcriptional level IGFBP-3 mRNA expression was downregulated in the livers of HP group piglets. Finally, DNA hypermethylation and higher enrichment of the histone repressive marks H3K27me3 and H3K9me3 were observed. CONCLUSIONS: Taken together, these results suggest that a maternal high-protein diet during gestation epigenetically reprograms IGFBP-3 gene expression to modulate the hepatic growth axis in weaning piglets.

Bioactive mesoporous silica nanoparticle-functionalized titanium implants with controllable antimicrobial peptide release potentiate the regulation of inflammation and osseointegration.

Bacterial infection and delayed osseointegration are two major challenges for titanium-based orthopedic implants. In the present study, we developed a functionalized titanium implant Ti-M@A by immobilizing antimicrobial peptide (AMP) HHC36-loaded diselenide-bridged mesoporous silica nanoparticles (MSNs) on the surface, which showed good long-term and mechanical stability. The functionalized implants can realize the sustained release of AMP over 30 days and exhibit over 95.71 % antimicrobial activity against four types of clinical bacteria (S. aureus, E. coli, P. aeruginosa and MRSA), which arose from the capability to destroy the bacterial membranes. Moreover, Ti-M@A can efficiently inhibit the biofilm formation of the bacteria. The functionalized implants can also significantly promote the osteogenic differentiation of mouse bone marrow-derived mesenchymal stem cells (mBMSCs) because of the Se in MSNs. Notably, it can trigger macrophages toward M2 polarization in vitro by scavenging ROS in LPS-activated macrophages. Consequently, in vivo assays with infection and non-infection bone defect models demonstrated that such bioactive implants can not only kill over 98.82 % of S. aureus, but also promote osseointegration. Hence, this study provides a combined strategy to resolve bacterial infection and delayed osseointegration for titanium implants.

Dynamic surface adapts to multiple service stages by orchestrating responsive polymers and functional peptides.

Control over the implant surface functions is highly desirable to enhance tissue healing outcomes but has remained unexplored to adapt to the different service stages. In the present study, we develop a smart titanium surface by orchestrating thermoresponsive polymer and antimicrobial peptide to enable dynamic adaptation to the implantation stage, normal physiological stage and bacterial infection stage. The optimized surface inhibited bacterial adhesion and biofilm formation during surgical implantation, while promoted osteogenesis in the physiological stage. The further temperature increase driven by bacterial infection induced polymer chain collapse to expose antimicrobial peptides by rupturing bacterial membranes, as well as protect the adhered cells from the hostile environment of infection and abnormal temperature. The engineered surface could inhibit infection and promote tissue healing in rabbit subcutaneous and bone defect infection models. This strategy enables the possibility to create a versatile surface platform to balance bacteria/cell-biomaterial interactions at different service stages of implants that has not been achieved before.

Unraveling the whole genome DNA methylation profile of zebrafish kidney marrow by Oxford Nanopore sequencing.

Zebrafish is a widely used model organism for investigating human diseases, including hematopoietic disorders. However, a comprehensive methylation baseline for zebrafish primary hematopoietic organ, the kidney marrow (KM), is still lacking. We employed Oxford Nanopore Technologies (ONT) sequencing to profile DNA methylation in zebrafish KM by generating four KM datasets, with two groups based on the presence or absence of red blood cells. Our findings revealed that blood contamination in the KM samples reduced read quality and altered methylation patterns. Compared with whole-genome bisulfite sequencing (WGBS), the ONT-based methylation profiling can cover more CpG sites (92.4% vs 70%-80%), and exhibit less GC bias with more even genomic coverage. And the ONT methylation calling results showed a high correlation with WGBS results when using shared sites. This study establishes a comprehensive methylation profile for zebrafish KM, paving the way for further investigations into epigenetic regulation and the development of targeted therapies for hematopoietic disorders.

Marriage of High-Throughput Gradient Surface Generation With Statistical Learning for the Rational Design of Functionalized Biomaterials.

Functional biomaterial is already an important aspect in modern therapeutics; yet, the design of novel multi-functional biomaterial is still a challenging task nowadays. When several biofunctional components are present, the complexity that arises from their combinations and interactions will lead to tedious trial-and-error screening. In this work, a novel strategy of biomaterial rational design through the marriage of gradient surface generation with statistical learning is presented. Not only can parameter combinations be screened in a high-throughput fashion, but also the optimal conditions beyond the experimentally tested range can be extrapolated from the models. The power of the strategy is demonstrated in rationally designing an unprecedented ternary functionalized surface for orthopedic implant, with optimal osteogenic, angiogenic, and neurogenic activities, and its optimality and the best osteointegration promotion are confirmed in vitro and in vivo, respectively. The presented strategy is expected to open up new possibilities in the rational design of biomaterials.