Formation mechanism and characterization of porous biomass carbon for excellent performance lithium-ion batteries

Porous biomass carbon derived from corn stalks was prepared via carbonization and activation of CaCl₂. Combined with its microstructure, the formation mechanism and electrochemical properties were analyzed. The addition of CaCl₂ was the key factor to form the porous structure, and the proportion of CaCl₂ had a significant impact on the pores distribution and electrochemical properties. The resulting sample had a specific surface area of 370.6 m² g⁻¹ and an average pore size of 9.65 nm. The sample was circulated at 0.2C for 100 cycles, the specific discharge capacity was 783 mA h g⁻¹. After 60 cycles at different rates, when the current was restored to 0.2C again, the discharge specific capacity quickly recovered. This showed that the sample had excellent rate performance and cycle stability for lithium-ion batteries.

Porous biomass carbon derived from corn stalks was prepared via carbonization and activation of CaCl₂.     

乙肝后肝硬化患者局灶性脑白质高信号与轻微型肝性脑病相关性的MRI研究

目的探讨乙肝后肝硬化患者局灶性脑白质高信号(white matter hyperintensity,WMH)与轻微型肝性脑病(minimal hepatic encephalopathy,MHE)的关系。材料与方法前瞻性收集在我院就诊的乙肝后肝硬化患者38例,其中包括无肝性脑病(non hepatic encephalopathy,n HE)20例,MHE 18例。所有受试者接受神经心理学测验、血液生化检查以及头部磁共振扫描。由2名神经影像医师根据液体衰减反转恢复序列图像评估受试者局灶性WMH的有无及严重程度:Fazekas量表评分0~1分为无或轻度局灶性WMH,Fazekas量表评分≥2分为中重度局灶性WMH。比较n HE与MHE两组间年龄、性别、肝硬化病程、肝功能Child-Pugh分级、静脉血氨浓度、局灶性WMH有无及严重程度的差异;采用多因素logistic回归分析肝硬化患者伴发MHE的独立预测因素;采用Spearman等级相关分析肝硬化患者局灶性WMH与认知功能的相关性。结果在年龄、性别匹配的前提下,MHE组与n HE组相比,中重度局灶性WMH的患者更多,差异有统计学意义(P0.01);肝硬化病程、肝功能Child-Pugh分级、静脉血氨浓度在两组间差异无统计学意义(P值均0.05)。多因素logistic回归分析表明中重度局灶性WMH是肝硬化患者伴发MHE的独立预测因素(OR=18.62,95%CI:2.43~142.86;P0.05)。Spearman等级相关显示:肝硬化患者局灶性WMH的严重程度与数字连接测验-A的完成时间呈显著正相关(r=0.617,P0.01),与数字符号测验及数字广度测验评分呈显著负相关(r=-0.695,P0.01;r=-0.558,P0.01)。结论肝硬化患者的中重度局灶性WMH是MHE的独立预测因素,提示患者可能伴发MHE。     

Combination Immunotherapy of MUC1 mRNA Nano-vaccine and CTLA-4 Blockade Effectively Inhibits Growth of Triple Negative Breast Cancer

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Cardiac function in patients with polymyositis or dermatomyositis: a three-dimensional speckle-tracking echocardiography study

Cardiac event is a major cause of death in patients with idiopathic inflammatory myopathies (IIM). The most frequent IIMs are polymyositis (PM) and dermatomyositis (DM). The purpose of this study was to analyze cardiac involvement by three-dimensional speckle-tracking echocardiography (3D STE) in patients with PM or DM, and to identify the relationship of cardiac injury with clinical characteristics and disease-specific parameters. 60 PM/DM patients with preserved left ventricular ejection fraction and 30 matched healthy controls were assessed by conventional echocardiography, 3D STE with biventricular strain analysis and electrocardiogram. Compared to controls, patients with PM/DM had significantly diminished left ventricular global longitudinal systolic strain and right ventricular longitudinal systolic strain (LVGLS, ? 20.3?±?2.5 vs. ? 23.4?±?1.7%; RVLS, ? 19.4?±?4.2 vs ? 24.8?±?2.0%; both P?<?0.001), and longer QTc intervals(421.0?±?38.4 vs 400.6?±?14.5 ms, P?=?0.001). Multiple regression analysis showed that Myositis Damage Index (MDI) was independently associated with LVGLS (R²?=?0.44, P?=?0.002) and RVLS (R²?=?0.56, P?<?0.001) in PM/DM patients with established disease course more than 1 year. In multivariate analysis of pooled data for all the PM/DM patients, when MDI was excluded due to missing observations, disease duration correlated with worse LVGLS (R²?=?0.24, P?=?0.002), while concomitant interstitial lung disease correlated with worse RVLS (R²?=?0.30, P?<?0.001). Disease activity scores (Myositis Intention to Treat Activities Index) had a weak positive correlation with QTc intervals (r_sp = 0.31, P?=?0.02). Our results suggest that cardiac injury in PM/DM is a long-term process and its severity depends on patients’ heterogeneous clinical features and systemic disease burden.     

Detection of noisy rectangular targets in high spatial resolution images

Human-related targets in high-spatial-resolution images often present rectangular shapes, such as most buildings, farmland, etc. However, their edges often encounter bending or missing parts as well as redundancy, making them difficult to detect by current breaking-assembling strategies that initially detect line segments and then gather them into potential rectangles. We propose a rectangle-detection method that uses a whole-object detection strategy that detects rectangles as integrated units to avoid these problems. Comparison experiments with a state-of-the-art method on both synthesized and high-spatial-resolution images indicate that our method performs well in detecting rectangles both in accuracy and time-cost aspects, especially when the edges are noisy.