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(2...     

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...     

Clinical significance and prevalence of anti-Saccharomyces cerevisiae antibody in Chinese patients with primary biliary cirrhosis

Clinical significance of anti-Saccharomyces cerevisiae antibody (ASCA) and its prevalence in Chinese primary biliary cirrhosis (PBC) patients have not been characterized and therefore needs to be defined. Enzyme-linked immunosorbent assay was used to test ASCA in sera from 198 PBC patients, 85 patients with other liver diseases (OLD) and 35 health controls (HC). Indirect immunofluorescence was used to detect anti-mitochondrial antibodies (AMA) in PBC. Results showed that the frequency of ASCA in PBC, 29.8 %, was higher than other disease groups. And ASCA occurred more frequently in PBC patients with positive anti-gp210 than the negative ones. Also, ASCA was detected in 7 out of 15 PBC negative for AMA. Some liver-related biochemical indices and inflammatory indices were significantly higher in PBC patients with positive ASCA (p < 0.05). In conclusion, the prevalence of ASCA in Chinese PBC patients is 29.8 %. PBC patients with positive ASCA are associated with more severe liver injury, and ASCA-IgA might be related to disease activity of PBC.     

机器人与腹腔镜手术治疗造口旁疝18例临床分析

目的探讨达芬奇机器人和腹腔镜微创手术在造口旁疝治疗中的应用。 方法回顾性分析2018年4月至2022年4月在福建医科大学附属协和医院使用达芬奇机器人系统和腹腔镜行微创造口旁疝无张力修补术的18例患者资料。记录并比较两组手术时间、术中出血量、恢复进食时间、术后切口感染、麻痹性肠梗阻、引流管拔除时间、住院天数等,远期随访指标包括复发、补片感染、慢性疼痛。 结果18例均顺利完成造口旁疝无张力修补术,合并行造口重建术4例（22.2%）。Sugarbaker法修补13例（72.2%）,其中使用达芬奇机器人系统2例,使用腹腔镜11例;Keyhole法修补5例（27.7%）,其中使用达芬奇机器人系统1例,使用腹腔镜4例。手术时间191~406 min,平均（276.8±71.3）min。术中出血量20~100 ml,平均（29.3±22.2）ml。术后第2天恢复流质饮食,第3天进食半流质;放置引流管病例,术后5~7 d拔除引流管;常规腹带束缚3~6个月。术后住院时间3~19 d,平均（8.2±4.7）d。术后复发1例（5.6%）,切口感染1例（5.6%）,麻痹性肠梗阻3例（16.7%）,肺部感染6例（33.3%）,切口感染及麻痹性肠梗阻病例均经过非手术治疗后痊愈出院。随访期间均未出现复发、补片感染、慢性疼痛。 结论使用达芬奇机器人系统和腹腔镜进行微创造口旁疝无张力修补术均安全可行,围手术期并发症少,术后恢复快,疗效确切。