Although it is generally accepted that amino acids were present on the prebiotic Earth, the mechanism by which a-amino acids were condensed into polypeptides before the emergence of enzymes remains unsolved. Here,w ed emonstrate aprebiotically plausible mechanismfor peptide (amide) bond formation that is enabled by a-hydroxy acids,which were likely present along with amino acids on the early Earth. Together, a-hydroxy acids and a-amino acids form depsipeptides-oligomers with ac ombination of ester and amide linkages-in model prebiotic reactions that are driven by wet-cool/dry-hot cycles.T hrough ac ombination of esteramide bond exchange and ester bond hydrolysis,depsipeptides are enriched with amino acids over time.These results support al ong-standing hypothesis that peptides might have arisen from ester-based precursors.

MiRNAs are a class of small non‐coding RNAs that are involved in the development and progression of various complex diseases. Great efforts have been made to discover potential associations between miRNAs and diseases recently. As experimental methods are in general expensive and time‐consuming, a large number of computational models have been developed to effectively predict reliable disease‐related miRNAs. However, the inherent noise and incompleteness in the existing biological datasets have inevitably limited the prediction accuracy of current computational models. To solve this issue, in this paper, we propose a novel method for miRNA‐disease association prediction based on matrix completion and label propagation. Specifically, our method first reconstructs a new miRNA/disease similarity matrix by matrix completion algorithm based on known experimentally verified miRNA‐disease associations and then utilizes the label propagation algorithm to reliably predict disease‐related miRNAs. As a result, MCLPMDA achieved comparable performance under different evaluation metrics and was capable of discovering greater number of true miRNA‐disease associations. Moreover, case study conducted on Breast Neoplasms further confirmed the prediction reliability of the proposed method. Taken together, the experimental results clearly demonstrated that MCLPMDA can serve as an effective and reliable tool for miRNA‐disease association prediction.

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TGF-β has pleiotropic effects on many cell types at different stages of their development, including mast cells. The present study examines the effects of TGF-β on human skin mast cells of the MCTC type. The expression of TGF-β receptors (TGF-R) was verified at the mRNA and protein levels for TGF-RI and TGF-RII, and at the mRNA level for accessory molecules β-glycan and endoglin. TGF-β did not affect mast cell viability after 1 wk at concentrations ≤10 ng/ml, but at 50 ng/ml caused significant cell death. TGF-β inhibited surface and total expression of Kit in a dose-dependent manner, whereas the surface expression of FcεRI, FcγRI, and FcγRII was not affected. TGF-β inhibited degranulation and cytokine production, but not PGD2 production. TGF-β diminished surface Kit expression through a TGF-RI kinase/Smad-dependent pathway by inhibiting new synthesis of Kit protein, which became evident following internalization and degradation of Kit after mast cells were exposed to the Kit ligand, stem cell factor. In contrast, addition of TGF-β had no discernible effect on surface Kit expression when administered 3 days after stem cell factor, by which time surface Kit levels had returned to baseline. Although both transcription and translation are important for de novo expression of Kit, Kit mRNA levels were not affected by TGF-β. Therefore, transcription of a gene other than Kit might be involved in Kit expression. Finally, activation of mast cells increased their susceptibility to TGF-β-mediated apoptosis, a process that might regulate the survival of activated mast cells in vivo.