Targeting orthotopic gliomas with renal-clearable luminescent gold nanoparticles

A major clinical translational challenge in nanomedicine is the potential of toxicity associated with the uptake and long-term retention of non-degradable nanoparticles (NPs) in major organs.The development of inorganic NPs that undergo renal clearance could potentially resolve this significant biosafety concern.However,it remains unclear whether inorganic NPs that can be excreted by the kidneys remain capable of targeting tumors with poor permeability.Glioblastoma multiforme,the most malignant orthotopic brain tumor,presents a unique challenge for NP delivery because of the blood-brain barrier and robust blood-tumor barrier of reactive microglia and macroglia in the tumor microenvironment.Herein,we used an orthotopic murine glioma model to investigate the passive targeting of glutathione-coated gold nanoparticles (AuNPs) of 3 nm in diameter that undergo renal clearance and 18-nm AuNPs that fail to undergo renal clearance.Remarkably, we report that 3-nm AuNPs were able to target intracranial tumor tissues with higher efficiency (2.3x relative to surrounding non-tumor normal brain tissues) and greater specificity (3.0x)than did the larger AuNPs.Pharmacokinetics studies suggested that the higher glioma targeting ability of the 3-nm AuNPs may be attributed to the longer retention time in circulation.The total accumulation of the 3-nm AuNPs in major organs was significantly less (8.4x) than that of the 18-nm AuNPs.Microscopic imaging of blood vessels and renal-clearable AuNPs showed extravasation of NPs from the leaky blood-tumor barrier into the tumor interstitium.Taken together,our results suggest that the 3-nm AuNPs,characterized by enhanced permeability and retention,are able to target brain tumors and undergo renal clearance.     

In situ trapped high-density single metal atoms within graphene: Iron-containing hybrids as representatives for efficient oxygen reduction

Nano Research - Atomically dispersed catalysts have attracted attention in energy conversion applications because their efficiency and chemoselectivity for special catalysis are superior to those...     

基于粗糙集的一体化保障技术属性约简问题研究

一体化保障技术是目前提高复杂武器系统测试和保障能力的研究重点,为解决一体化保障技术中存在的指标冗余问题,结合粗糙集相关理论,提出了基于属性重要性和属性间影响度的约简算法;通过在某型一体化保障设备的柴油发电机子模块中应用该算法,在精简测试指标的同时,保证了较高的测试准确性,缩短了测试时间,验证并说明该理论可以有效地解决一体化保障技术中的指标冗余问题。     

Composition-Controllable Syntheses and Property Modulations from 2D Ferromagnetic Fe5Se8 to Metallic Fe3Se4 Nanosheets

Exploring new-type 2D magnetic materials with high magnetic transition temperature and robust air stability has attracted wide attention for developing innovative spintronic devices. Recently, intercalation of native metal atoms into the van der Waals gaps of 2D layered transition metal dichalcogenides (TMDs) has been developed to form 2D non-layered magnetic TMDs, while only succeeded in limited systems (e.g., Cr₂S₃, Cr₅Te₈). Herein, composition-controllable syntheses of 2D non-layered iron selenide nanosheets (25% Fe-intercalated triclinic Fe₅Se₈ and 50% Fe-intercalated monoclinic Fe₃Se₄) are firstly reported, via a robust chemical vapor deposition strategy. Specifically, the 2D Fe₅Se₈ exhibits intrinsic room-temperature ferromagnetic property, which is explained by the change of electron spin states from layered 1T'-FeSe₂ to non-layered Fe-intercalated Fe₅Se₈ based on density functional theory calculations. In contrast, the ultrathin Fe₃Se₄ presents novel metallic features comparable with that of metallic TMDs. This work hereby sheds light on the composition-controllable synthesis and fundamental property exploration of 2D self-intercalation induced novel TMDs compounds, by propelling their application explorations in nanoelectronics and spintronics-related fields.     

Accurate localization of cortical convolutions in MR brain images

Analysis of brain images often requires accurate localization of cortical convolutions. Although magnetic resonance (MR) brain images offer sufficient resolution for identifying convolutions in theory, the nature of tomographic imaging prevents clear definition of convolutions in individual slices. Existing methods for solving this problem rely on heuristic adaptation of brain atlases created from a small number of individuals. These methods do not usually provide high accuracy because of large biological variations among individuals. The authors propose to localize convolutions by linking realistic visualizations of the cortical surface with the original image volume. They have developed a system so that a user can quickly localize key convolutions in several visualizations of an entire brain surface. Because of the links between the visualizations and the original volume, these convolutions are simultaneously localized in the original image slices. In the process of the authors' development, they have implemented a fast and easy method for visualizing cortical surfaces in MR images, thereby making their scheme usable in practical applications.     

基于确定性测试图形的BIST构建方法

为降低内建自测试(Build-in Self Test,BIST)的测试功耗,提出了一种基于确定性测试图形的内建自测试构建方法:首先采用D算法生成测试所需的测试图形,然后使用粒子群算法对其进行优化,使内建自测试的功耗大幅度降低;文中最后以ISCAS'85Benchmark中的部分电路作为实验对象,并给出了测试图形优化前后的功耗数;实验结果证明该方法能够有效降低内建自测试的测试功耗,并且具有方法简单、无需额外硬件开销的特点.