No abstract

Adipose-derived stem cells (ADSCs) and their secretomes mediate diverse skin-regeneration effects, such as wound-healing and antioxidant protection, that are enhanced by hypoxia. We investigated the hair-growth-promoting effect of conditioned medium (CM) of ADSCs to determine if ADSCs and their secretomes regenerate hair and if hypoxia enhances hair regeneration. If so, we wanted to identify the factors responsible for hypoxia-enhanced hair-regeneration. We found that ADSC-CM administrated subcutaneously induced the anagen phase and increased hair regeneration in C 3 H/NeH mice. In addition, ADSC-CM increased the proliferation of human follicle dermal papilla cells (HFDPCs) and human epithelial keratinocytes (HEKs), which are derived from two major cell types present in hair follicles. We investigated the effect of hypoxia on ADSC function using the same animal model in which hypoxia increased hair regrowth. Forty-one growth factors in ADSC-CM from cells cultured under hypoxic or normoxic conditions were analyzed. The secretion of insulin-like growth factor binding protein (IGFBP)-1, IGFBP-2, macrophage colony-stimulating factor (M-CSF), M-CSF receptor, platelet-derived growth factor receptor-β, and vascular endothelial growth factor was significantly increased by hypoxia, while the secretion of epithelial growth factor production was decreased. It is reasonable to conclude that ADSCs promote hair growth via a paracrine mechanism that is enhanced by hypoxia.

generation tasks, such as generation from various downsampling factors, multi-domain image translation, paint-toimage, and editing with scribbles.

Notable progress has been made in the therapeutic and research applications of cyclic peptides since our previous review. New drugs based on cyclic peptides are entering the market, such as plecanatide, a cyclic peptide approved by the United States Food and Drug Administration in 2017 for the treatment of chronic idiopathic constipation. In this review, we discuss recent developments in stapled peptides, prepared with the use of chemical linkers, and bicyclic/tricyclic peptides with more than two rings. These have widespread applications for clinical and research purposes: imaging, diagnostics, improvement of oral absorption, enzyme inhibition, development of receptor agonist/antagonist, and the modulation of protein-protein interaction or protein-RNA interaction. Many cyclic peptides are expected to emerge as therapeutics and biochemical tools.

The growth in the number of Android and Internet of Things (IoT) devices has witnessed a parallel increase in the number of malicious software (malware), calling for new analysis approaches. We represent binaries using their graph properties of the Control Flow Graph (CFG) structure and conduct an in-depth analysis of malicious graphs extracted from the Android and IoT malware to understand their differences. Using 2,874 and 2,891 malware binaries corresponding to IoT and Android samples, we analyze both general characteristics and graph algorithmic properties. Using the CFG as an abstract structure, we then emphasize various interesting findings, such as the prevalence of unreachable code in Android malware, noted by the multiple components in their CFGs, and larger number of nodes in the Android malware, compared to the IoT malware, highlighting a higher order of complexity. We implement a Machine Learning based classifiers to detect IoT malware from benign ones, and achieved an accuracy of 97.9% using Random Forests (RF).