As the outermost barrier of the body, skin is a major target of oxidative stress. In the brain, estrogen has been reported synthesized locally and protects neurons from oxidative stress. Here, we explored whether estrogen is also locally synthesized in the skin to protect from oxidative stress and whether aberrant local estrogen synthesis is involved in skin disorders. Enzymes and estrogen receptor expression in skin cells were examined first by quantitative real-time PCR and Western blot analyses. Interestingly, the estrogen synthesis enzyme was mainly localized in epidermal keratinocytes and estrogen receptors were mainly expressed in melanocytes among 13 kinds of cultured human skin cells. The most abundant estrogen synthesis enzyme expressed in the epidermis was 17β-hydroxysteroid dehydrogenase 1 (HSD17β1) localized in keratinocytes, and the most dominant estrogen receptor expressed in the epidermis was G protein-coupled estrogen receptor 1 (GPER1) in melanocytes. To investigate whether keratinocyte-derived estradiol could protect melanocytes from oxidative stress, cultured human primary epidermal melanocytes (HEMn-MPs) were treated with H2O2 in the presence or absence of 17β estradiol or co-cultured with HSD17β1 siRNA-transfected keratinocytes. Keratinocyte-derived estradiol exhibited protective effects against H2O2-induced cell death. Further, reduced expression of HSD17β1 in the epidermis of skin from vitiligo patients was observed compared to the skin from healthy donors or in the normal portions of the skin in vitiligo patients. Our results suggest a possible new target for interventions that may be used in combination with current therapies for patients with vitiligo. 相似文献
Action recognition based on a human skeleton is an extremely challenging research problem. The temporal information contained in the human skeleton is more difficult to extract than the spatial information. Many researchers focus on graph convolution networks and apply them to action recognition. In this study, an action recognition method based on a two-stream network called RNXt-GCN is proposed on the basis of the Spatial-Temporal Graph Convolutional Network (ST-GCN). The human skeleton is converted first into a spatial-temporal graph and a SkeleMotion image which are input into ST-GCN and ResNeXt, respectively, for performing the spatial-temporal convolution. The convolved features are then fused. The proposed method models the temporal information in action from the amplitude and direction of the action and addresses the shortcomings of isolated temporal information in the ST-GCN. The experiments are comprehensively performed on the four datasets: 1) UTD-MHAD, 2) Northwestern-UCLA, 3) NTU RGB-D 60, and 4) NTU RGB-D 120. The proposed model shows very competitive results compared with other models in our experiments. On the experiments of NTU RGB?+?D 120 dataset, our proposed model outperforms those of the state-of-the-art two-stream models.
A technological milestone for experiments employing transition edge sensor bolometers operating at sub-Kelvin temperature is the deployment of detector arrays with 100s-1000s of bolometers. One key technology for such arrays is readout multiplexing: the ability to read out many sensors simultaneously on the same set of wires. This paper describes a frequency-domain multiplexed readout system which has been developed for and deployed on the APEX-SZ and South Pole Telescope millimeter wavelength receivers. In this system, the detector array is divided into modules of seven detectors, and each bolometer within the module is biased with a unique ~MHz sinusoidal carrier such that the individual bolometer signals are well separated in frequency space. The currents from all bolometers in a module are summed together and pre-amplified with superconducting quantum interference devices operating at 4 K. Room temperature electronics demodulate the carriers to recover the bolometer signals, which are digitized separately and stored to disk. This readout system contributes little noise relative to the detectors themselves, is remarkably insensitive to unwanted microphonic excitations, and provides a technology pathway to multiplexing larger numbers of sensors. 相似文献
Pest oxidation has been known for a long time in refractory transition-metal disilicides such as NbSi2 and MoSi2[1―4]. However, the origin of pesting reaction of these materials is still under debate. Although the pesting phenomenon in NbSi2 has been reported in several works[5―7], a direct study of the mechanism is scarce at the moment. Compared to NbSi2, pesting in MoSi2 has received relatively extensive attention. Mckamey et al.[8] showed fragmentation near 773K occurred easily in as… 相似文献
Massive amounts of biogas slurry are produced due to the development of biogas plants. The pollution features and the risk of biogas slurry were fully evaluated in this work. Thirty-one biogas slurry samples were collected from sixteen different cities and five different raw materials biogas plants (e.g. cattle manure, swine manure, straw-manure mixture, kitchen waste and chicken manure). The chemical oxygen demand (COD), ammonia nitrogen (NH4+ - N), anions (e.g. Cl-,SO42-, NO3- and PO4-3), antibiotics (e.g. sulphonamides, quinolones, β2-receptor agonists, macrolides, tetracyclines and crystal violet) and heavy metals (e.g. Cu, Cd, As, Cr, Hg, Zn and Pb) contents from these biogas slurry samples were systematically investigated. On this basis, risk assessment of biogas slurry was also performed. The concentrations of COD, NH4+ and PO4-3 in biogas slurry samples with chicken manure as raw material were significantly higher than those of other raw materials. Therefore, the biogas slurry from chicken manure raw material demonstrated the most serious eutrophication threat. The antibiotic contents in biogas slurry samples from swine manure were the highest among five raw materials, mostly sulphonamides, quinolones and tetracyclines. Biogas slurry revealed particularly serious arsenic contamination and moderate potential ecological risk. The quadratic polynomial stepwise regression model can quantitatively describe the correlation among NH4+ - N, PO4-3 and heavy metals concentration of biogas slurry. This work demonstrated a universal potential threat from biogas slurry that can provide supporting data and theoretical basis for harmless treatment and reuse of biogas slurry. 相似文献