EFFECTS OF HYPOXIC ENDOTHELIAL CELL CONDITIONED MEDIUM ON PROLIFERATION AND COLLAGEN SYNTHESIS OF SMOOTH MUSCLE CELLS AND INHIBITORY EFFECTS OF RADIX SALVIAE MILTIORRHIZAE

The effects of hypoxic endothelial cell conditioned medium (HECCM) on proliferation and collagen synthesis of cultured porcine pulmonary arterial smooth muscle cells (PASMCs) were studied by 3H-thymidine (3H-TdR) and 3H-proline incorporations, image analysis for determination of DNA content and colorimetric assay using MTT, and the inhibitory effects of radix salviae miltiorrhizae (RSM) on them were also investigated. The results showed that HECCM could induce enhancement of the enzymatic activity of mitochondria, increase of the nucleic DNA content and increases of the 3H-TdR and 3H-proline incorporations in PASMCs. The 3H-proline incorporation in PASMCs cultured in HECCM was 1.83 times as much as that cultured in normoxic endothelial cell conditioned medium (NECCM). Compared with the control, Chinese herb medicine RSM could inhibit the proliferation of PASMCs cultured in HECCM and decrease the 3H-prolinc incorporation in PASMCs cultured in both HECCM and NECCM (P< 0.001). However, RSM had no ef fects on the nucleic DNA content and 3H-TdR incorporation into DNA of PASMCs cultured in NECCM. It suggests that hypoxia may stimulate the endothelia to synthesize and secrete some cytokines which can stimulate the proliferation and the synthesis of collagen of PASMCs and RSM can inhibit this process.

Effects of Forming Conditions and TiC–TiB_2 Contents on the Microstructures of Self-Propagating High-Temperature Synthesized NiAl–TiC–TiB_2 Composites

The NiAl–TiC–TiB2 composites were processed by self-propagating high-temperature synthesis（SHS） method using raw powders of Ni, Al, Ti, B4 C, TiC, and TiB2, and their microstructure and micro-hardness were investigated. The TiC–TiB2 in NiAl matrix, with contents from 10 to 30 wt%, emerged with the use of two methods： in situ formed and externally added. The results show that all final products are composed of three phases of NiAl, TiC, and TiB2. The microstructures of NiAl–TiC–TiB2 composites with in situ-formed TiC and TiB2 are fine, and all the three phases are distributed uniformly. The grains of NiAl matrix in the composites have been greatly refined, and the micro-hardness of NiAl increases from 381 HV100 to 779 HV100. However, the microstructures of NiAl–TiC–TiB2 composites with externally added TiC and TiB2 are coarse and inhomogeneous, with severe agglomeration of TiC and TiB2 particles. The samples containing externally added 30 wt% TiC–TiB2attain the micro-hardness of 485 HV100. The microstructure evolution and fracture mode of the two kinds of NiAl–TiC–TiB2 composites are different.

Three-component synthesis of amidoalkyl naphthols catalyzed by bismuth(Ⅲ) nitrate pentahydrate

Bismuth（Ⅲ） nitrate pentahydrate catalyzed the three-component condensation ofβ-naphthol,aldehydes and amines/urea under solvent-free conditions to afford the corresponding amidoalkyl naphthols in excellent yields.

High fidelity virtual try-on network via semantic adaptation and distributed componentization

Image-based virtual try-on systems have significant commercial value in online garment shopping.However,prior methods fail to appropriately handle details,so are defective in maintaining the original appearance of organizational items including arms,the neck,and in-shop garments.We propose a novel high fidelity virtual try-on network to generate realistic results.Specifically,a distributed pipeline is used for simultaneous generation of organizational items.First,the in-shop garment is warped using thin plate splines(TPS)to give a coarse shape reference,and then a corresponding target semantic map is generated,which can adaptively respond to the distribution of different items triggered by different garments.Second,organizational items are componentized separately using our novel semantic map-based image adjustment network(SMIAN)to avoid interference between body parts.Finally,all components are integrated to generatethe overall result by SMIAN.A priori dual-modalinformation is incorporated in the tail layers of SMIAN to improve the convergence rate of the network.Experiments demonstrate that the proposed method can retain better details of condition information than current methods.Our method achieves convincing quantitative and qualitative results on existing benchmark datasets.