8,385 research outputs found

    Vaccination with Minigenes Encoding VH-derived Major Histocompatibility Complex Class I–binding Epitopes Activates Cytotoxic T Cells that Ablate Autoantibody-producing B Cells and Inhibit Lupus

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    Current treatments for autoantibody-mediated diseases, such as lupus, can cause nonspecific immune suppression. In this paper, we used a bioinformatic approach to identify major histocompatibility complex class I–binding epitopes in the heavy chain variable region of anti-DNA antibodies from lupus-prone (NZB/NZW F1) mice. Vaccination of such mice with plasmid DNA vectors encoding these epitopes induced CD8+ T cells that killed anti-DNA antibody-producing B cells, reduced serum anti-DNA antibody levels, retarded the development of nephritis, and improved survival. Vaccine-mediated induction of anti-VH cytotoxic T lymphocytes that ablate autoreactive B cells represents a novel approach to treat autoantibody-mediated diseases

    Neural2Speech: A Transfer Learning Framework for Neural-Driven Speech Reconstruction

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    Reconstructing natural speech from neural activity is vital for enabling direct communication via brain-computer interfaces. Previous efforts have explored the conversion of neural recordings into speech using complex deep neural network (DNN) models trained on extensive neural recording data, which is resource-intensive under regular clinical constraints. However, achieving satisfactory performance in reconstructing speech from limited-scale neural recordings has been challenging, mainly due to the complexity of speech representations and the neural data constraints. To overcome these challenges, we propose a novel transfer learning framework for neural-driven speech reconstruction, called Neural2Speech, which consists of two distinct training phases. First, a speech autoencoder is pre-trained on readily available speech corpora to decode speech waveforms from the encoded speech representations. Second, a lightweight adaptor is trained on the small-scale neural recordings to align the neural activity and the speech representation for decoding. Remarkably, our proposed Neural2Speech demonstrates the feasibility of neural-driven speech reconstruction even with only 20 minutes of intracranial data, which significantly outperforms existing baseline methods in terms of speech fidelity and intelligibility.Comment: To appear in 2024 IEEE International Conference on Acoustics, Speech and Signal Processin

    How do China’s lockdown and post-COVID-19 stimuli impact carbon emissions and economic output? Retrospective estimates and prospective trajectories

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    This paper develops a multi-sector and multi-factor structural gravity model that allows an analytical and quantitative decomposition of the emission and output changes into composition and technique effects. We find that the negative production shock of China's containment policy propagates globally via supply chains, with the carbon-intensive sectors experiencing the greatest carbon emission shocks. We further reveal that China's current stimulus package in 2021-2025 is consistent with China's emission intensity-reduction goals for 2025, but further efforts are required to meet China's carbon emissions-peaking target in 2030 and Cancun 2°C goal. Short-term changes in carbon emissions resulting from lockdowns and initial fiscal stimuli in "economic rescue" period have minor long-term effects, whereas the transitional direction of future fiscal stimulus exerts more predominant impact on long-term carbon emissions. The efficiency improvement effects are more important than the sectoral structure effects of the fiscal stimulus in achieving greener economic growth. [Abstract copyright: © 2022 The Author(s).

    An Intragenic SRF-Dependent Regulatory Motif Directs Cardiac-Specific microRNA-1-1/133a-2 Expression

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    Transcriptional regulation is essential for any gene expression including microRNA expression. MiR-1-1 and miR-133a-2 are essential microRNAs (miRs) involved in cardiac and skeletal muscle development and diseases. Early studies reveal two regulatory enhancers, an upstream and an intragenic, that direct the miR-1-1 and miR-133a-2 transcripts. In this study, we identify a unique serum response factor (SRF) binding motif within the enhancer through bioinformatic approaches. This motif is evolutionarily conserved and is present in a range of organisms from yeast, flies, to humans. We provide evidence to demonstrate that this regulatory motif is SRF-dependent in vitro by electrophoretic mobility shift assay, luciferase activity assay, and endogenous chromatin immunoprecipitation assay followed by DNA sequence confirmation, and in vivo by transgenic lacZ reporter mouse studies. Importantly, our transgenic mice indicate that this motif is indispensable for the expression of miR1-1/133a-2 in the heart, but not necessary in skeletal muscle, while the enhancer is sufficient for miR1-1/133a-2 gene expression in both tissues. The mutation of the motif alone completely abolishes miR-1-1/133a-2 gene expression in the animal heart, but not in the skeletal muscle. Our findings reveal an additional architecture of regulatory complex directing miR-1-1/133a-1 gene expression, and demonstrate how this intragenic enhancer differentially manages the expression of the two miRs in the heart and skeletal muscle, respectively
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