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Single-molecule lazer nanospectroscopy together with micro-electron voltage vitality solution.
Mechanistically, we identified MYB and ETV5 as downstream targets for ASXL1-MT and HHEX by using transcriptome and ChIP-seq analyses. Moreover, we found that expression of ASXL1-MT enhanced the binding of HHEX to the promoter loci of MYB or ETV5 via reducing H2AK119ub. Depletion of MYB or ETV5 induced apoptosis or differentiation in ASXL1-MT-expressing leukemia cells, respectively. In addition, ectopic expression of MYB or ETV5 reversed the reduced colony-forming activity of HHEX-depleted ASXL1-MT-expressing leukemia cells. These findings indicated that the HHEX-MYB/ETV5 axis promotes myeloid transformation in ASXL1-mutated preleukemia cells.Cranial irradiation (IR), an effective tool to treat malignant brain tumors, triggers a chronic pro-inflammatory microglial response, at least in the adult brain. Using single-cell and bulk RNA sequencing, combined with histology, we show that the microglial response in the juvenile mouse hippocampus is rapid but returns toward normal within 1 week. The response is characterized by a series of temporally distinct homeostasis-, sensome-, and inflammation-related molecular signatures. We find that a single microglial cell simultaneously upregulates transcripts associated with pro- and anti-inflammatory microglial phenotypes. Finally, we show that juvenile and adult irradiated microglia are already transcriptionally distinct in the early phase after IR. Our results indicate that microglia are involved in the initial stages but may not be responsible for driving long-term inflammation in the juvenile brain.Stringent lockdown measures implemented in Italy to mitigate the spread of COVID-19 are generating unprecedented economic impacts. However, the environmental consequences associated with the temporary shutdown and recovery of industrial and commercial activities are still not fully understood. Using the well-known carbon footprint (CF) indicator, this paper provides a comprehensive estimation of environmental effects due to the COVID-19 outbreak lockdown measures in Italy. Our aim was to quantify the CF associated with the consumption of energy by any economic activity and region in Italy during the lockdown, and then compare these environmental burdens with the CF calculated for analogous periods from 2015 to 2019 (~March and April). Complementarily, we also conducted a scenario analysis to estimate the post-lockdown CF impact in Italy. A consumption-based approach was applied according to the principles of the established Life Cycle Assessment method. The CF was therefore quantified as a sum of direct and indirect greenhouse gases (GHGs) released from domestically produced and imported energy metabolism flows, excluding the exports. Our findings indicate that the CF in the lockdown period is ~-20% lower than the mean CF calculated for the past. This means avoided GHGs in between ~5.6 and ~10.6 Mt CO2e. Results further suggest that a tendency occurs towards higher impact savings in the Northern regions, on average ~230 kt CO2e of GHGs avoided by province (against ~110-130 kt CO2e in central and Southern provinces). Not surprisingly, these are the utmost industrialized areas of Italy and have been the ones mostly affected by the outbreak. Despite our CF estimates are not free of uncertainties, our research offers quantitative insights to start understanding the magnitude generated by such an exceptional lockdown event in Italy on climate change, and to complement current scientific efforts investigating the relationships between air pollution and the spread of COVID-19.The formation of insoluble inclusions in the cytosol and nucleus is associated with impaired protein homeostasis and is a hallmark of several neurodegenerative diseases. Due to the absence of the autophagic machinery, nuclear protein aggregates require a solubilization step preceding degradation by the 26S proteasome. Using yeast, we identify a nuclear protein quality control pathway required for the clearance of protein aggregates. The nuclear J-domain protein Apj1 supports protein disaggregation together with Hsp70 but independent of the canonical disaggregase Hsp104. Disaggregation mediated by Apj1/Hsp70 promotes turnover rather than refolding. A loss of Apj1 activity uncouples disaggregation from proteasomal turnover, resulting in accumulation of toxic soluble protein species. Endogenous substrates of the Apj1/Hsp70 pathway include both nuclear and cytoplasmic proteins, which aggregate inside the nucleus upon proteotoxic stress. These findings demonstrate the coordinated activity of the Apj1/Hsp70 disaggregation system with the 26S proteasome in facilitating the clearance of toxic inclusions inside the nucleus.Although recent deep learning methodology has shown promising performance in fast imaging, the network needs to be retrained for specific sampling patterns and ratios. Therefore, how to explore the network as a general prior and leverage it into the observation constraint flexibly is urgent. selleck inhibitor In this work, we present a multi-channel enhanced Deep Mean-Shift Prior (MEDMSP) to address the highly under-sampled magnetic resonance imaging reconstruction problem. By extending the naive DMSP via integration of multi-model aggregation and multi-channel network learning, a high-dimensional embedding network derived prior is formed. Then, we apply the learned prior to single-channel image reconstruction via variable augmentation technique. The resulting model is tackled by proximal gradient descent and alternative iteration. Experimental results under various sampling trajectories and acceleration factors consistently demonstrated the superiority of the proposed prior.While the properties of surfaces and interfaces are crucial to modern devices, they are commonly difficult to explore since the signal from the bulk often masks the surface contribution. Here we introduce a methodology based on scanning electron microscopy (SEM) coupled with a pulsed laser source, which offers the capability to sense the topmost layer of materials, to study the surface photovoltage (SPV) related effects. This method relies on a pulsed optical laser to transiently induce an SPV and a continuous primary electron beam to produce secondary electron (SE) emission and monitor the change of the SE yield under laser illumination. We observe contrasting behaviors of the SPV-induced SE yield change on n-type and p-type semiconductors. We further study the dependence of the SPV-induced SE yield on the primary electron beam energy, the optical fluence, and the modulation frequency of the optical excitation, which reveal the details of the dynamics of the photocarriers in the presence of the surface built-in potential.
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