Massive rearrangements of cellular MicroRNA signatures are key drivers of hepatocyte dedifferentiation

Hepatocytes are dynamic cells that, upon injury, can alternate between nondividing differentiated and dedifferentiated proliferating states in vivo . However, in two‐dimensional cultures, primary human hepatocytes (PHHs) rapidly dedifferentiate, resulting in loss of hepatic functions that significantly limits their usefulness as an in vitro model of liver biology, liver diseases, as well as drug metabolism and toxicity. Thus, understanding the underlying mechanisms and stalling of the dedifferentiation process would be highly beneficial to establish more‐accurate and relevant long‐term in vitro hepatocyte models. Here, we present comprehensive analyses of whole proteome and transcriptome dynamics during the initiation of dedifferentiation during the first 24 hours of culture. We report that early major rearrangements of the noncoding transcriptome, hallmarked by increased expression of small nucleolar RNAs, long noncoding RNAs, microRNAs (miRNAs), and ribosomal genes, precede most changes in coding genes during dedifferentiation of PHHs, and we speculated that these modulations could drive the hepatic dedifferentiation process. To functionally test this hypothesis, we globally inhibited the miRNA machinery using two established chemically distinct compounds, acriflavine and poly‐l ‐lysine. These inhibition experiments resulted in a significantly impaired miRNA response and, most important, in a pronounced reduction in the down‐regulation of hepatic genes with importance for liver function. Thus, we provide strong evidence for the importance of noncoding RNAs, in particular, miRNAs, in hepatic dedifferentiation, which can aid the development of more‐efficient differentiation protocols for stem‐cell‐derived hepatocytes and broaden our understanding of the dynamic properties of hepatocytes with respect to liver regeneration. Conclusion: miRNAs are important drivers of hepatic dedifferentiation, and our results provide valuable information regarding the mechanisms behind liver regeneration and possibilities to inhibit dedifferentiation in vitro

Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system

Oligodendrocytes have been considered as a functionally homogeneous population in the central nervous system (CNS). We performed single-cell RNA sequencing on 5072 cells of the oligodendrocyte lineage from 10 regions of the mouse juvenile and adult CNS. Thirteen distinct populations were identified, 12 of which represent a continuum from Pdgfra(+) oligodendrocyte precursor cells (OPCs) to distinct mature oligodendrocytes. Initial stages of differentiation were similar across the juvenile CNS, whereas subsets of mature oligodendrocytes were enriched in specific regions in the adult brain. Newly formed oligodendrocytes were detected in the adult CNS and were responsive to complex motor learning. A second Pdgfra(+) population, distinct from OPCs, was found along vessels. Our study reveals the dynamics of oligodendrocyte differentiation and maturation, uncoupling them at a transcriptional level and highlighting oligodendrocyte heterogeneity in the CNS

Homogeneously catalysed conversion of aqueous formaldehyde to H2 and carbonate

Small organic molecules provide a promising solution for the requirement to store large amounts of hydrogen in a future hydrogen-based energy system. Herein, we report that diolefin–ruthenium complexes containing the chemically and redox non-innocent ligand trop2dad catalyse the production of H2 from formaldehyde and water in the presence of a base. The process involves the catalytic conversion to carbonate salt using aqueous solutions and is the fastest reported for acceptorless formalin dehydrogenation to date. A mechanism supported by density functional theory calculations postulates protonation of a ruthenium hydride to form a low-valent active species, the reversible uptake of dihydrogen by the ligand and active participation of both the ligand and the metal in substrate activation and dihydrogen bond formation

Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions: Survey and Analysis

We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV, and ULLIV). In addition, we show how the subspace-based algorithms can be analyzed and compared by means of simple FIR filter interpretations. The algorithms are illustrated with working Matlab code and applications in speech processing