祛风除湿法治疗IgA肾病的Meta分析

目的:IgA肾病是以系膜区IgA沉积为主要特征的原发性肾小球疾病,异常IgA1的免疫复合物沉积及RAAS系统激活与其发病关系密切。目前主要使用ACEI或ARB类药物及糖皮质激素或联合免疫抑制剂治疗。近年来中医药在IgA肾病的防治中发挥了巨大的作用,其中祛风除湿法治疗IgA肾病成为关注的焦点,在西医治疗基础上联用祛风除湿的中药在提高临床疗效、减少蛋白尿、减轻血尿、保护肾功能方面效果显著,同时也可减轻激素及免疫抑制剂所产生的不良反应,逐渐被临床认可。但由于目前现有的研究样本量小,文献质量较低,很难被广泛接受,迫切需要科学的研究方法为临床提供充分的证据支持,所以本研究拟通过Meta分析,综合分析祛风除湿法治疗IgA肾病的临床疗效及安全性评估。方法:检索中文数据库包括中国知网、万方、维普及英文数据库包括PubMed、Cochrane Library及手工检索相关领域期刊杂志中关于祛风除湿法治疗风湿内扰型IgA肾病的随机对照试验。采用Cochrane协助网提供的RevMan 5.3软件进行Meta分析,主要研究指标为有效率、24 h尿蛋白定量、血肌酐、血清白蛋白、肾小球滤过率、中医证候积分评估及不良反应发生率。结果:通过计算机检索中英文数据库及手工检索中医肾病相关领域期刊杂志,共检索出197篇文献,然后逐一阅读题目及摘要、泛读及精读全文后排除主题不相关文献,排除回顾性研究、假随机、半随机、重复文献、会议论文、不符合纳入标准文献,最后纳入8篇随机对照试验,共826例患者进行研究。Meta分析结果显示在西医治疗基础上联合祛风除湿的方药比单纯西医治疗在提高临床疗效(OR=3.35,95%CI［2.20,5.10］,P<0.000 01)、降低24 h尿蛋白定量(MD=-0.46,95%CI［-0.76,-0.17］,P=0.002)、提高白蛋白(MD=4.95,95%CI［3.62,6.28］,P<0.000 01),减少不良反应发生率方面(OR=0.42,95%CI［0.22,0.80］,P=0.008)效果显著,差异均有统计学意义。而血肌酐(MD=-4.82,95%CI［-12.27,2.63］,P=0.20)、肾小球滤过率(MD=-0.63,95%CI［-4.26,2.99］,P=0.73)、中医证候积分方面(MD=-1.96,95%CI［-3.98,0.05］,P=0.06)差异均无统计学意义。结论:在西医基础上联合祛风除湿的方药治疗IgA肾病比单纯西医治疗,在提高临床有效率、降低蛋白尿、提高白蛋白、减少不良反应的发生方面效果显著,差异均有统计学意义。但此次纳入文献样本量小,文献质量均不高,未来需要更科学可靠的循证医学方法进一步完善祛风除湿法治疗IgA肾病的临床研究。     

Least-cost targets and avoided fossil fuel capacity in India’s pursuit of renewable energy

India has set aggressive targets to install more than 400 GW of wind and solar electricity generation by 2030, with more than two-thirds of that capacity coming from solar. This paper examines the electricity and carbon mitigation costs to reliably operate India’s grid in 2030 for a variety of wind and solar targets (200 GW to 600 GW) and the most promising options for reducing these costs. We find that systems where solar photovoltaic comprises only 25 to 50% of the total renewable target have the lowest carbon mitigation costs in most scenarios. This result invites a reexamination of India’s proposed solar-majority targets. We also find that, compared to other regions and contrary to prevailing assumptions, meeting high renewable targets will avoid building very few new fossil fuel (coal and natural gas) power plants because of India’s specific weather patterns and need to meet peak electricity demand. However, building 600 GW of renewable capacity, with the majority being wind plants, reduces how often fossil fuel power plants run, and this amount of capacity can hold India’s 2030 emissions below 2018 levels for less than the social cost of carbon. With likely wind and solar cost declines and increases in coal energy costs, balanced or wind-majority high renewable energy systems (600 GW or ≈ 45% share by energy) could result in electricity costs similar to a fossil fuel-dominated system. As an alternative strategy for meeting peak electricity demand, battery storage can avert the need for new fossil fuel capacity but is cost effective only at low capital costs (≈ USD 150 per kWh).

India emitted 3.2 billion metric tons of CO₂e in 2016, or 6% of annual global greenhouse gas emissions, placing it third only to China and the United States (1). One-third of these emissions were from coal-based electricity. At the same time, both per capita emissions and energy use remain well below global averages, suggesting a massive potential for growth of electricity generation and emissions (1). India’s primary energy demand is expected to double by 2040 compared to 2017 (2). Whether this energy comes from fossil or low-carbon sources will significantly affect the ability to limit average global temperature rise to below 2 °C.India is already pursuing significant technology-specific renewable energy targets—100 GW of solar and 60 GW of wind by 2022—and, in its Nationally Determined Contributions (NDC), committed to a 40% target for installed generation capacity from nonfossil fuel sources by 2030 (3). In 2019, in part to fulfill its NDC commitment, the Indian government proposed to install 440 GW of renewable energy capacity by 2030, with 300 GW of solar and 140 GW of wind capacity (4). Although costs of solar photovoltaic (PV) and wind technologies have declined significantly in recent years (5–7), the low cost of coal and integration costs associated with variable renewable energy (VRE) technologies like wind and solar may hinder India’s cost-effective transition to a decarbonized electricity system. This paper seeks to answer a number of questions that arise in the Indian context. What targets for wind and solar capacity have the lowest associated integration costs? Will these targets significantly offset the need to build fossil fuel generation capacity? What additional measures can we take to mitigate VRE integration costs?Merely comparing the levelized costs of VRE with the costs of conventional generation ignores additional cost drivers, which depend on the timing of VRE production and other conditions in the power system (8, 9). Quantifying these drivers requires models that choose lowest-cost generation capacity portfolios and simulate optimal system operation with detailed spatiotemporal data. Several prior studies address these system-level integration costs in a capacity expansion planning framework (10–16), often making decisions based on a limited sample of representative hours. Other studies explicitly estimate the relationship between long-run economic value (including integration costs) of VRE penetration levels (17, 18) but do not include VRE investment costs in their analysis. Few prior studies explore the impacts of high VRE penetration on India’s electricity system, and those that do either use the capacity expansion framework and do not evaluate the economic value of multiple VRE targets (4, 19, 20) or do not optimize capacity build around proposed VRE targets (21).Here we address this gap by estimating how different VRE targets affect the cost to reliably operate the Indian electricity system. To do so, we work with three interrelated models. First, using a spatially explicit model for VRE site selection, we identify the lowest levelized cost wind and solar sites to meet different VRE capacity targets, and study how the resource quality—and corresponding levelized cost—of selected sites changes with increasing VRE targets.Second, using a capacity investment model that accounts for VRE production patterns and optimal dispatch of hydropower and battery storage, we determine the capacity requirements and investment costs for coal, combined cycle gas turbines (CCGT), and combustion turbine (CT) peaker plants. Due to uncertainties in their future deployment (22), and because their current targets are relatively low (4), we did not consider new nuclear or hydro capacity in the main scenarios but include those in the sensitivity scenarios presented in SI Appendix, section 2. Third, we use a unit commitment and economic dispatch model to simulate hourly operation of the electricity system and estimate annual system operational costs. This model captures important technical constraints, including minimum operating levels, daily unit commitment for coal and natural gas plants, and energy limits on hydropower and battery storage. Rather than cooptimize VRE capacity, we compute the system-level economic value of a range of VRE targets by comparing the sum of the avoided new conventional capacity and energy generation costs to a no-VRE scenario. The net cost for a scenario is then the difference between the levelized cost of the VRE and the system-level economic value. Materials and Methods provides more detail on this process.Our results show that, despite greater levelized cost reduction forecasts for solar PV compared to wind technologies, VRE targets with greater amounts of wind have the lowest projected net carbon mitigation costs. This finding is robust to a range of scenarios, including low-cost solar and storage, and lower minimum generation levels for coal generators.We find that, although VRE production displaces energy production from conventional generators, it does very little to defer the need for capacity from those generators due to low correlation between VRE production and peak demand. Our findings suggest that VRE in India avoids far less conventional capacity than VRE in other regions in the world. These capacity requirements are slightly mitigated if India’s demand patterns evolve to more closely resemble demand in its major cities. Overall, we conclude that the importance of choosing the right VRE mix is significant when measured in terms of carbon mitigation costs: Whereas most solar-majority scenarios we examined lead to costs greater than or equal to estimates of the social cost of carbon (SCC), wind-majority mixes all cost far less than the SCC.     

裘昌林教授从伏风宿痰辨治神经系统“怪病”

[目的]总结裘昌林教授诊疗神经系统“怪病”的临床经验。[方法]通过复习相关中医文献、跟师临证、整理医案等方式，总结裘师治疗神经系统疑难病的病因病机、辨治思路、用药特色，并举验案一则以示临床应用。[结果]裘师认为，伏风内潜系“怪病”的病因，宿痰内停为“怪病”之夙根，风痰合而为患故见“奇证”，治疗上以搜风豁痰为大法，将涤痰汤作为搜风豁痰的基础方，在此基础上对平时深潜体内之伏风，适量选用虫类药搜风通络以增强临床疗效。所举验案中患儿辨证为肝旺脾虚、风痰阻络，经豁痰息风、清热平肝治疗后，收效良好。[结论]神经系统“怪病”因反复发作，严重影响患者的生活质量。裘昌林教授从伏风宿痰辨治神经系统“怪病”，经验独到，值得临床推广。     

当归饮子对血虚风燥型湿疹模型幼鼠的影响及作用机制＊

目的 研究当归饮子对血虚风燥型湿疹模型幼鼠的影响并探讨其作用机制。方法 采用2，4-二硝基氯苯（DNCB）、乙酰苯肼（APH）结合物理刺激制备血虚风燥湿疹模型，50只SD大鼠随机分为空白组、模型组、当归饮子高剂量组（30 g·kg^-1）、当归饮子低剂量组（15 g·kg^-1）、地氯雷他定组（0.8 mg·kg^-1），连续灌胃15天。观察幼鼠体重、脾脏指数、胸腺指数；通过湿疹皮损评分、HE染色组织病理学改变评价当归饮子对血虚风燥湿疹的治疗效果；采用酶联免疫吸附法（ELISA）检测血清γ-干扰素（IFN-γ）、白介素-4（IL-4）、免疫球蛋白E（IgE）、白三烯B4（LTB4）、白三烯C4（LTC4）含量；采用逆转录聚合酶链式反应（RT-PCR）检测皮肤组织半胱氨酰白三烯受体1（CysLTR1）和半胱氨酰白三烯受体2（CysLTR2）表达水平，以探索当归饮子治疗血虚风燥湿疹的作用机制。结果 与正常组相比，模型组幼鼠体重明显减轻（P<0.05），脾脏指数增大、胸腺指数减小（P<0.05）；幼鼠背部出现红斑、糜烂、渗出、水肿、鳞屑等皮损；病理学呈现大量中性粒细胞浸润、表皮海绵水肿、角化过度伴角化不全；IFN-γ水平下降（P<0.05），IL-4、IgE、LTB4、LTC4水平及皮肤CysLTR1和CysLTR2受体表达水平上调（P<0.01）。与模型组相比，当归饮子高、低剂量组及地氯雷他定组体重均明显上升（P<0.05），脾脏指数减小、胸腺指数增大（P<0.05）；皮损均明显改善（P<0.05），病理改变呈表皮炎症消失，真皮乳头水肿消失；IFN-γ水平显著上升（P<0.05），IL-4、IgE、LTB4、LTC4水平明显下降（P<0.05）；皮肤CysLTR1和CysLTR2受体表达水平均明显下降（P<0.05），其中以当归饮子高剂量组最为明显（P<0.05）。结论 当归饮子治疗血虚风燥型湿疹模型幼鼠疗效明显，机制可能与其调控湿疹幼鼠Thl／Th2失衡、下调血清LTB4、LTC4水平及皮肤CysLTR1、CysLTR2受体表达水平有关。