A High-Phosphorus Diet Moderately Alters the Lipidome and Transcriptome in the Skeletal Muscle of Adult Mice.

A high phosphorus intake has been associated with various metabolic disorders, including chronic kidney disease, cardiovascular disease, and osteoporosis. Recent studies have demonstrated the effects of dietary phosphorus on lipid and glucose metabolism. This study investigated the impact of a high-phosphorus diet on mouse skeletal muscle lipid composition and gene transcription. Adult male mice (n = 12/group) received either a diet with an adequate (0.3%) or a high (1.2%) phosphorus concentration for 6 weeks. The lipidome analysis showed that among the 17 analyzed lipid classes, the concentrations of three classes were reduced in the high phosphorus group compared to the adequate phosphorus group. These classes were phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and lysophosphatidylcholine (LPC) (p < 0.05). Out of the three hundred and twenty-three individual lipid species analyzed, forty-nine showed reduced concentrations, while three showed increased concentrations in the high phosphorus group compared to the adequate phosphorus group. The muscle transcriptome analysis identified 142 up- and 222 down-regulated transcripts in the high phosphorus group compared to the adequate phosphorus group. Gene set enrichment analysis identified that genes that were up-regulated in the high phosphorus group were linked to the gene ontology terms "mitochondria" and "Notch signaling pathway", whereas genes that were down-regulated were linked to the "PI3K-AKT pathway". Overall, the effects of the high-phosphorus diet on the muscle lipidome and transcriptome were relatively modest, but consistently indicated an impact on lipid metabolism.

Interface engineering for high-performance, triple-halide perovskite-silicon tandem solar cells.

Improved stability and efficiency of two-terminal monolithic perovskite-silicon tandem solar cells will require reductions in recombination losses. By combining a triple-halide perovskite (1.68 electron volt bandgap) with a piperazinium iodide interfacial modification, we improved the band alignment, reduced nonradiative recombination losses, and enhanced charge extraction at the electron-selective contact. Solar cells showed open-circuit voltages of up to 1.28 volts in p-i-n single junctions and 2.00 volts in perovskite-silicon tandem solar cells. The tandem cells achieve certified power conversion efficiencies of up to 32.5%.

Model-based identification of TNFα-induced IKKß-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds.

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.