非霍奇金淋巴瘤85例临床及预后分析

目的：分析多种因素对非霍奇金淋巴瘤(NHL)预后的影响。方法：通过SABC法进行免疫分型，采用Kaplan—Meier法分析患者治疗后的生存期，采用Cox比例风险模型分析影响预后的因素。结果：B细胞来源-NHL(B-NHL)发病率为63．3％。T细胞来源-NHL(T—NHL)为36．7％；低度恶性占17．6％，中、高度恶性占74．1％。1、2、3、5年生存率：低度恶性患者为92．1％、84．5％、65．1％、45．1％；中、高度恶性患者为84．9％、67．5％、47．6％、28．4％。I、Ⅱ期患者为98．8％、91.5％、87．5％、70．3％；Ⅲ期、Ⅳ期患者为62．1％、55．5％、40．1％、23．8％。T—NHL为70．8％、53．5％、47．7％、30．2％；B-NHL为82．1％、70．5％、61．1％、50．1％。结论：年龄、乳酸脱氢酶水平、恶性程度、临床分期、免疫分型、身体状况评分(PS)是影响NHL预后的重要因素。     

端脑髓突的断面解剖学观测

目的：通过对端脑髓突支数及其分支的研究，探讨端脑髓突与脑回的对应关系，指导脑回的医学影像学定位。材料与方法：随机采用３０个颅脑标本，经ＣＴ扫描后锯切出相应断面，结合断面标本及其相应的ＣＴ影像表现对端脑髓突进行综合观测。结果：端脑髓突清晰而易于辨认，各髓突对应相应的脑回皮质。端脑髓突的支数在不同端脑层面上明显变化，但侧别差异无显著性意义。结论：只有熟悉端脑髓突的支数及其分支等情况，才能认准端脑髓突，     

输尿管狭窄的应用解剖学研究

目的:探讨输尿管生理狭窄的数目、位置及狭窄的程度,为选择性CT分段扫描诊断输尿管结石提供解剖学依据.方法:解剖30例国人成人尸体60条输尿管(男40条,女20条),分段观测输尿管形态、狭窄的数目、位置和管腔内径.结果:各段输尿管形态多样,主要有四类.输尿管生理狭窄的程度依次为膀胱壁内段＞输尿管盆段＞输尿管髂血管段＞输尿管腹段.结论:输尿管生理狭窄的数目不恒定.生理狭窄的部位除膀胱壁内段外其余部位均不恒定,膀胱壁内段狭窄程度最大.     

纤维状矿物粉尘对肺泡巨噬细胞膜损伤的机制研究

评价来自全国６个不同矿床的６种纤维矿物粉尘的细胞膜毒性,探讨其受损机制,采用体外细胞培养技术及扫描电镜方法观察纤维状矿物粉尘对肺泡巨噬细胞膜的通透性、膜流动性、膜形成的影响。结果纤维硅灰石,斜发沸石无细胞膜毒性,纤状海泡石、纤状坡缕石、纤状水镁石、纤状蛇纹石石棉表现出不同程度的细胞膜毒性。纤维状矿物粉尘对细胞膜毒性与其表面特性有关     

Assessment of battery utilization and energy consumption in the large-scale development of urban electric vehicles

Electrifying transportation in the form of the large-scale development of electric vehicles (EVs) plays a pivotal role in reducing urban atmospheric pollution and alleviating fossil fuel dependence. However, the rising scale of EV deployment is exposing problems that were previously hidden in small-scale EV applications, and the lack of large-scale EV operating data deters relevant explorations. Here, we report several issues related to the battery utilization and energy consumption of urban-scale EVs by connecting three unique datasets of real-world operating states of over 3 million Chinese EVs, operational data, and vehicle feature data. Meanwhile, by incorporating climatic data and EV data outside China, we extend our models to several metropolitan areas worldwide. We find that blindly increasing the battery energy of urban EVs could be detrimental to sustainable development. The impact of changes in the energy consumption of EVs would be exacerbated in large-scale EV utilization, especially during seasonal shifts. For instance, even with a constant monthly driving demand, the average energy consumption of Beijing light-duty EVs would change by up to 21% during winter–spring shifts. Our results may also prove useful for research on battery resources, urban power supply, environmental impacts, and policymaking.

Large-scale electrification of transport is considered an effective solution to decrease the use of petroleum-derived fuels and mitigate the urban accumulation of air pollutants. The global stock of light-duty electric vehicles (LDEVs) exceeded 7.2 million in 2019 (1, 2), and China accounted for the largest share at ∼47%, followed by Europe and the United States. To further boost the electric vehicle (EV) market, numerous jurisdictions have introduced incentives or adopted action plans: China has prolonged subsidies for EVs to 2022 (3); the European Union has provided new tax schemes for electric cars (4); and several regions in the United States and Canada, such as California and Quebec, respectively, have enacted incentives for zero-emission vehicle programs (5, 6). The International Energy Agency indicated that the global EV stock would need to increase to 140 million by 2030 (2) to achieve the goals of existing government policies [the Stated Policies Scenario (7)]. In this context, from 2019 to 2030, the global battery capacity production and electricity demand from EVs would soar ninefold to 1.5 TWh ⋅ y⁻¹ and sixfold to 550 TWh ⋅ y⁻¹, respectively (2, 8). Accordingly, the global demand for the critical metals used in EV batteries, including cobalt, lithium, manganese, and nickel, would increase by 8 to 14 times from 2019 to 2030 (2, 9).The surging demand for battery resources and energy from EVs signifies a need to reassess the real-world battery utilization and energy consumption of urban-scale EVs. Research topics on this front have focused on analyzing the supply risks of battery resources (10–12), battery recycling (13–15), sustainability (16–18), charging planning (19–21), and the impact on urban power grids (22–24). A common and indispensable input of these studies is accurate battery utilization or energy consumption of urban EVs. Meanwhile, since the environmental gains of EVs can only be measured from electricity production processes, the energy consumption of urban EVs is also an important basis for research on emissions (25–28), air pollution (29, 30), and health benefits (31, 32). However, owing to the absence of urban-scale EV operating data, most existing assessments are conducted by relying on macroscopic evaluations or the simulations that are calibrated with aggregate-level parameters (33–35). When applied to large-scale EV applications, these simplifications can lead to nonnegligible biases in the results (36) as they cannot reflect the complexity of driving trajectories and varying battery performance in EV operation. On the other hand, in small-scale EV samples, the overall levels of battery utilization and energy consumption tend to be altered by the special use behavior of individual users. This phenomenon conceals some trends that would otherwise have been evident, such as low battery utilization and seasonal changes in the energy consumption of EVs.In 2016, the National Monitoring and Management Center for New Energy Vehicles was established in China, which serves as the national big data platform for EVs. The center has the only datasets in the world that contain real-time operating data of nationwide EVs (the number of EVs in the datasets exceeded 3 million in 2020). For the EVs in some metropolitan areas in China, such as Beijing and Shanghai, the coverage of the platform can reach up to 80%. The data content primarily includes two parts: dynamic vehicular data (general vehicle status, subsystem operating data, and location data) and static information (metadata and attributes). The temporal and spatial resolutions of the dynamic vehicular data are 1 to 30 s and 1 to 10 m, respectively. This large-scale and high-precision data source of Chinese EVs, coupled with EV datasets outside China, provides unique data support for achieving the large-scale assessments in this work (see Materials and Methods).Here, we present a fact-based assessment of battery utilization and energy consumption in urban-scale EV applications to expose several issues affecting battery resources and the urban power supply. To this end, we combine four types of data: 1) EV operating data, 2) EV operational data describing the fleet types and license plate regions, 3) vehicle feature data providing the specifications of EVs, and 4) climate data providing ambient temperatures in different urban areas (see Materials and Methods). To understand the impact of regional variability, nine metropolitan areas worldwide with large EV markets (37) are selected in this work. Accordingly, we first analyze the changes in battery utilization that are affected by user behavior or limited by current battery technology. We investigate how different fleet types and climatic conditions can affect the battery utilization of urban EVs. We also display the developing trends of battery utilization in urban-scale EV groups under different directions of battery technology improvement. Then, we assess the energy consumption of urban EVs from different perspectives. We observe that in some continental climate regions, the energy consumption of EVs fluctuates greatly in different months because of temperature shifts. These fluctuations and step changes are unfavorable as they can greatly amplify the original daily energy demand of EVs, especially in urban-scale EVs. We show the extent to which this problem can be addressed as EV technology improves. The results demonstrate how often-ignored changes in the battery utilization and energy consumption of urban EVs could affect the resource efficiency of EV batteries and urban power supply.     

电导滴定法测定氨基化磁性微球表面氨基含量

目的建立电导滴定法测定磁性微球表面微量氨基的化学计量点选择新方法,定量分析其氨基含量,为其表面修饰及偶联奠定基础。方法观察不同因素对滴定结果准确度的影响,在此基础上采用电导滴定法对磁性微球表面氨基进行定量测定,比较曲线拟合及电导率的变化率(ΔK)确定化学计量点2种不同方法对滴定结果的影响。结果建立了更为直接、客观的电导滴定法测定磁性微球表面微量氨基的新方法。利用滴定曲线拟合计算氨基化磁性微球表面氨基含量为(35.05±14.18)μmol/g(RSD=40.47%,n=5);而用ΔK确定化学计量点计算氨基化磁性微球表面氨基含量为(51.38±2.91)μmol/g(RSD=5.66%,n=5),后者的测定精度明显高于前者。结论利用电导率的变化率(ΔK)确定滴定拐点更为直接客观,降低了主观误差,测定精度较高。     

Three new inflammatory markers C reactive protein to albumin ratio,neutrophil to lymphocyte ratio,and platelet to lymphocyte ratio correlated with relapsing polychondritis disease activity index

Clinical Rheumatology - The novel inflammatory markers C-reactive protein to albumin ratio (CAR), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR) were associated with...     

Variation of red blood cell parameters in Behcet’s disease: association with disease severity and vascular involvement

Clinical Rheumatology - Behcet’s disease (BD) is a systemic and chronic inflammatory vasculitis with unknown etiology. Diagnosis is determined by evaluating several clinical criteria, but the...     

The clinical and laboratory features associated with cancer in patients with primary biliary cholangitis: a longitudinal survey–based study

Clinical Rheumatology - To analyze the clinical and laboratory features of primary biliary cholangitis (PBC) patients complicated with cancer, and explore the potential factors associated with...     

系统性硬化症患者血浆C1q水平与ESR水平的相关性

目的 探讨系统性硬化症(SSc)患者和健康对照者血浆中C1 q的水平,以及C1 q水平与红细胞沉降率(ESR)和C反应蛋白(CRP)水平的关系.方法 测定137例SSc患者和105例健康对照者血浆C1q的水平,同时比较ESR和CRP升高或正常组的SSc患者的C1q水平.结果 SSc患者的血浆C1q水平高于健康对照者(208.84±44.85 mg/L vs 193.90±27.63 mg/L,P=0.002).然而,弥漫型皮肤SSc患者和局限型皮肤SSc患者的血浆C1q水平相似(208.39±38.30 mg/L vs 213.08±50.91 mg/L,P=0.67).ESR升高组的SSc患者的血浆C1q水平显著高于ESR正常组的SSc患者的血浆C1q水平(224.79±48.99 mg/L vs 193.12±33.97 mg/L,P=2.44×10-5),但CRP升高组和正常组的SSc患者的血浆C1q水平相似(221.29±58.07 mg/L vs 205.19±39.79 mg/L,P=0.079).C1q水平与ESR水平呈正相关(r=0.415,P=4.45×10-7),而C1q水平与CRP水平无显著相关性.结论 SSc患者血浆C1q水平高于健康对照者,且血浆C1q水平与ESR水平呈正相关.