Dynamic placement of the linker histone H1 associated with nucleosome arrangement and gene transcription in early Drosophila embryonic development

The linker histone H1 is critical to maintenance of higher-order chromatin structures and to gene expression regulation. However, H1 dynamics and its functions in embryonic development remain unresolved. Here, we profiled gene expression, nucleosome positions, and H1 locations in early Drosophila embryos. The results show that H1 binding is positively correlated with the stability of beads-on-a-string nucleosome organization likely through stabilizing nucleosome positioning and maintaining nucleosome spacing. Strikingly, nucleosomes with H1 placement deviating to the left or the right relative to the dyad shift to the left or the right, respectively, during early Drosophila embryonic development. H1 occupancy on genic nucleosomes is inversely correlated with nucleosome distance to the transcription start sites. This inverse correlation reduces as gene transcription levels decrease. Additionally, H1 occupancy is lower at the 5\u27 border of genic nucleosomes than that at the 3\u27 border. This asymmetrical pattern of H1 occupancy on genic nucleosomes diminishes as gene transcription levels decrease. These findings shed new lights into how H1 placement dynamics correlates with nucleosome positioning and gene transcription during early Drosophila embryonic development

Development of virtual reality support to factory layout planning

Virtual reality (VR) technology has become ever mature today with affordable and yet powerful hardware. In the manufacturing industry, there is a growing interest of adopting VR to improve existing work procedures. Factory layout planning (FLP) is a long standing area in production engineering that sees great potentials of VR integration. Virtual reality supported layout planning (VLP) is gaining wider attention in research and practice as the virtual environment allows designers to test out “what if” scenarios in relative ease. However, previous research of VLP mostly focus on general layout planning but not the detailed level planning. Also, it is reported that the virtual modeling process is time-consuming and costly. In this study, we propose a point cloud based virtual factory modelling approach for the VLP tasks. It incorporates point cloud representation of physical environment with CAD data to model the virtual factory with the aims of simplifying the modelling process and improving decision-making for the VLP tasks. The proposed approach is exemplified and refined through three industrial cases. The implementations and results of the cases are highlighted and discussed in details. At the end, a general guidance for VLP is extracted and presented for future point cloud based VR support in FLP tasks

Perturbed Adaptive Belief Propagation Decoding for High-Density Parity-Check Codes

Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This article aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding for high-density parity-check (HDPC) algebraic codes, such as Reed-Solomon (RS) codes, Bose-Chaudhuri-Hocquenghem (BCH) codes, and product codes. The key idea of traditional ABP is to sparsify certain columns of the parity-check matrix corresponding to the least reliable bits with small log-likelihood-ratio (LLR) values. This sparsification strategy may not be optimal when some bits have large LLR magnitudes but wrong signs. Motivated by this observation, we propose a Perturbed ABP (P-ABP) to incorporate a small number of unstable bits with large LLRs into the sparsification operation of the parity-check matrix. In addition, we propose to apply partial layered scheduling or hybrid dynamic scheduling to further enhance the performance of P-ABP. Simulation results show that our proposed decoding algorithms lead to improved error correction performances and faster convergence rates than the prior-art ABP variants

Optimized code design for constrained DNA data storage with asymmetric errors

With ultra-high density and preservation longevity, deoxyribonucleic acid (DNA)-based data storage is becoming an emerging storage technology. Limited by the current biochemical techniques, data might be corrupted during the processes of DNA data storage. A hybrid coding architecture consisting of modified variable-length run-length limited (VL-RLL) codes and optimized protograph low-density parity-check (LDPC) codes is proposed in order to suppress error occurrence and correct asymmetric substitution errors. Based on the analyses of the different asymmetric DNA sequencer channel models, a series of the protograph LDPC codes are optimized using a modified extrinsic information transfer algorithm (EXIT). The simulation results show the better error performance of the proposed protograph LDPC codes over the conventional good codes and the codes used in the existing DNA data storage system. In addition, the theoretical analysis shows that the proposed hybrid coding scheme stores ~1.98 bits per nucleotide (bits/nt) with only 1% gap from the upper boundary (2 bits/nt)

YAP1 withdrawal in hepatoblastoma drives therapeutic differentiation of tumor cells to functional hepatocyte-like cells

BACKGROUND and AIMS: Despite surgical and chemotherapeutic advances, the five-year survival rate for Stage IV Hepatoblastoma (HB), the predominant pediatric liver tumor, remains at 27%. YAP1 and beta-Catenin co-activation occurs in 80% of children\u27s HB; however, a lack of conditional genetic models precludes tumor maintenance exploration. Thus, the need for a targeted therapy remains unmet. Given the predominance of YAP1 and beta-Catenin activation in HB, we sought to evaluate YAP1 as a therapeutic target in HB. APPROACH and RESULTS: We engineered the first conditional HB murine model using hydrodynamic injection to deliver transposon plasmids encoding inducible YAP1(S127A) , constitutive beta-Catenin(DelN90) , and a luciferase reporter to murine liver. Tumor regression was evaluated using bioluminescent imaging, and tumor landscape characterized using RNA and ATAC sequencing, and DNA foot-printing. Here we show that YAP1(S127A) withdrawal mediates \u3e90% tumor regression with survival for 230+ days in mice. YAP1 (S127A) withdrawal promotes apoptosis in a subset of tumor cells and in remaining cells induces a cell fate switch driving therapeutic differentiation of HB tumors into Ki-67 negative hbHep cells with hepatocyte-like morphology and mature hepatocyte gene expression. YAP1 (S127A) withdrawal drives formation of hbHeps by modulating liver differentiation transcription factor (TF) occupancy. Indeed, tumor-derived hbHeps, consistent with their reprogrammed transcriptional landscape, regain partial hepatocyte function and rescue liver damage in mice. CONCLUSIONS: YAP1(S127A) withdrawal, without silencing oncogenic beta-Catenin, significantly regresses hepatoblastoma, providing the first in vivo data to support YAP1 as a therapeutic target for HB. YAP1(S127A) withdrawal alone sufficiently drives long-term regression in hepatoblastoma because it promotes cell death in a subset of tumor cells and modulates transcription factor occupancy to reverse the fate of residual tumor cells to mimic functional hepatocytes