197 research outputs found

    Role of Exosomal Noncoding RNAs in Lung Carcinogenesis

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    Lung cancer is the major cause of cancer death worldwide. Novel, recently discovered classes of noncoding RNAs (ncRNAs) have diverse functional and regulatory activities and increasing evidence suggests crucial roles for deregulated ncRNAs in the onset and progression of cancer, including lung cancer. Exosomes are small extracellular membrane vesicles of endocytic origin that are released by many cells and are found in most body fluids. Tumor-derived exosomes mediate tumorigenesis by facilitating tumor growth and metastasis. MicroRNAs (miRNAs) are a subclass of ncRNAs that are present in exosomes. miRNAs are taken up by neighboring or distant cells and modulate various functions of recipient cells. Here, we review exosome-derived ncRNAs with a focus on miRNAs and their role in lung cancer biology

    MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

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    Over the past few decades, multimodal emotion recognition has made remarkable progress with the development of deep learning. However, existing technologies are difficult to meet the demand for practical applications. To improve the robustness, we launch a Multimodal Emotion Recognition Challenge (MER 2023) to motivate global researchers to build innovative technologies that can further accelerate and foster research. For this year's challenge, we present three distinct sub-challenges: (1) MER-MULTI, in which participants recognize both discrete and dimensional emotions; (2) MER-NOISE, in which noise is added to test videos for modality robustness evaluation; (3) MER-SEMI, which provides large amounts of unlabeled samples for semi-supervised learning. In this paper, we test a variety of multimodal features and provide a competitive baseline for each sub-challenge. Our system achieves 77.57% on the F1 score and 0.82 on the mean squared error (MSE) for MER-MULTI, 69.82% on the F1 score and 1.12 on MSE for MER-NOISE, and 86.75% on the F1 score for MER-SEMI, respectively. Baseline code is available at https://github.com/zeroQiaoba/MER2023-Baseline

    Prediction of high-Tc superconductivity in ternary lanthanum borohydrides

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    The study of superconductivity in compressed hydrides is of great interest due to measurements of high critical temperatures (Tc) in the vicinity of room temperature, beginning with the observations of LaH10 at 170-190 GPa. However, the pressures required for synthesis of these high Tc superconducting hydrides currently remain extremely high. Here we show the investigation of crystal structures and superconductivity in the La-B-H system under pressure with particle-swarm intelligence structure searches methods in combination with first-principles calculations. Structures with six stoichiometries, LaBH, LaBH3, LaBH4, LaBH6, LaBH7 and LaBH8, were predicted to become stable under pressure. Remarkably, the hydrogen atoms in LaBH8 were found to bond with B atoms in a manner that is similar to that in H3S. Lattice dynamics calculations indicate that LaBH7 and LaBH8 become dynamically stable at pressures as low as 109.2 and 48.3 GPa, respectively. Moreover, the two phases were predicted to be superconducting with a critical temperature (Tc) of 93 K and 156 K at 110 GPa and 55 GPa, respectively. Our results provide guidance for future experiments targeting new hydride superconductors with both low synthesis pressures and high Tc.Comment: 16 pages, 5 figures

    Measurement report: Molecular characteristics of cloud water in southern China and insights into aqueous-phase processes from Fourier transform ion cyclotron resonance mass spectrometry

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    Characterizing the molecular composition of cloud water could provide unique insights into aqueous chemistry. Field measurements were conducted at Mt. Tianjing in southern China in May, 2018. There are thousands of formulas (C5−30_{5-30}H4−55_{4-55}O1−15_{1-15}N0−2_{0-2}S0−2_{0-2}) identified in cloud water by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). CHON formulas (formulas containing C, H, O, and N elements; the same is true for CHO and CHOS) represent the dominant component (43.6 %–65.3 % of relative abundance), followed by CHO (13.8 %–52.1%). S-containing formulas constitute ∼5 %–20 % of all assigned formulas. Cloud water has a relative-abundance-weighted average O/C of 0.45–0.56, and the double bond equivalent of 5.10–5.70. Most of the formulas (>85 %) are assigned as aliphatic and olefinic species. No statistical difference in the oxidation state is observed between cloud water and interstitial PM2.5_{2.5}. CHON with aromatic structures are abundant in cloud water, suggesting their enhanced in-cloud formation. Other organics in cloud water are mainly from biomass burning and oxidation of biogenic volatile organic compounds. The cloud water contains more abundant CHON and CHOS at night, which are primarily contributed by −N2_{2}O5_{5} function and organosulfates, demonstrating the enhanced formation in dark aqueous or multi-phase reactions. While more abundant CHO is observed during the daytime, likely due to the photochemical oxidation and photolysis of N- or S-containing formulas. The results provide an improved understanding of the in-cloud aqueous-phase reactions

    Engineering human ventricular heart muscles based on a highly efficient system for purification of human pluripotent stem cell-derived ventricular cardiomyocytes

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    Background Most infarctions occur in the left anterior descending coronary artery and cause myocardium damage of the left ventricle. Although current pluripotent stem cells (PSCs) and directed cardiac differentiation techniques are able to generate fetal-like human cardiomyocytes, isolation of pure ventricular cardiomyocytes has been challenging. For repairing ventricular damage, we aimed to establish a highly efficient purification system to obtain homogeneous ventricular cardiomyocytes and prepare engineered human ventricular heart muscles in a dish. Methods The purification system used TALEN-mediated genomic editing techniques to insert the neomycin or EGFP selection marker directly after the myosin light chain 2 (MYL2) locus in human pluripotent stem cells. Purified early ventricular cardiomyocytes were estimated by immunofluorescence, fluorescence-activated cell sorting, quantitative PCR, microelectrode array, and patch clamp. In subsequent experiments, the mixture of mature MYL2-positive ventricular cardiomyocytes and mesenchymal cells were cocultured with decellularized natural heart matrix. Histological and electrophysiology analyses of the formed tissues were performed 2 weeks later. Results Human ventricular cardiomyocytes were efficiently isolated based on the purification system using G418 or flow cytometry selection. When combined with the decellularized natural heart matrix as the scaffold, functional human ventricular heart muscles were prepared in a dish. Conclusions These engineered human ventricular muscles can be great tools for regenerative therapy of human ventricular damage as well as drug screening and ventricular-specific disease modeling in the future. Electronic supplementary material The online version of this article (doi:10.1186/s13287-017-0651-x) contains supplementary material, which is available to authorized users
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