基于生态系统服务和生态系统健康的生态风险评价——以长株潭城市群为例

基于生态系统服务和生态系统健康的生态风险评估框架为城市群生态风险管理和国土生态修复提供新的视角。以生态风险评估框架为基础,综合运用生态系统服务、生态系统健康评估模型以及相关分析法对长株潭城市群展开生态风险评价,并对风险程度进行分类。结果表明:(1)城市群的城市化水平提升,区域生态风险也随之增加。生态系统服务价值、生态系统组织、生态系统活力、生态系统弹性等生态指数呈现下降趋势。(2)人工表面比率和生态指数之间的Pearson相关系数表明,人工表面比率与生态指数之间存在负相关关系,人工表面比率是生态风险提升的关键因素。(3)城市群人工表面比率要控制在36%以下,以进行生态风险管理和国土生态修复。总的来说,评价框架可以作为区域生态风险的评价终点。     

Integrated evaluation of targeted and non-targeted therapies in a network meta-analysis

Individualized therapies for patients with biomarkers are moving more and more into the focus of research interest when developing new treatments. Hereby, the term individualized (or targeted) therapy denotes a treatment specifically developed for biomarker-positive patients. A network meta-analysis model for a binary endpoint combining the evidence for a targeted therapy from individual patient data with the evidence for a non-targeted therapy from aggregate data is presented and investigated. The biomarker status of the patients is either available at patient-level in individual patient data or at study-level in aggregate data. Both types of biomarker information have to be included. The evidence synthesis model follows a Bayesian approach and applies a meta-regression to the studies with aggregate data. In a simulation study, we address three treatment arms, one of them investigating a targeted therapy. The bias and the root-mean-square error of the treatment effect estimate for the subgroup of biomarker-positive patients based on studies with aggregate data are investigated. Thereby, the meta-regression approach is compared to approaches applying alternative solutions. The regression approach has a surprisingly small bias even in the presence of few studies. By contrast, the root-mean-square error is relatively greater. An illustrative example is provided demonstrating implementation of the presented network meta-analysis model in a clinical setting.     

Effect of sterol structure on ordered membrane domain (raft) stability in symmetric and asymmetric vesicles

Sterol structure influences liquid ordered domains in membranes, and the dependence of biological functions on sterol structure can help identify processes dependent on ordered domains. In this study we compared the effect of sterol structure on ordered domain formation in symmetric vesicles composed of mixtures of sphingomyelin, 1, 2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and cholesterol, and in asymmetric vesicles in which sphingomyelin was introduced into the outer leaflet of vesicles composed of DOPC and cholesterol. In most cases, sterol behavior was similar in symmetric and asymmetric vesicles, with ordered domains most strongly stabilized by 7-dehydrocholesterol (7DHC) and cholesterol, stabilized to a moderate degree by lanosterol, epicholesterol and desmosterol, and very little if at all by 4-cholesten-3-one. However, in asymmetric vesicles desmosterol stabilized ordered domain almost as well as cholesterol, and to a much greater degree than epicholesterol, so that the ability to support ordered domains decreased in the order 7-DHC > cholesterol > desmosterol > lanosterol > epicholesterol > 4-cholesten-3-one. This contrasts with values for intermediate stabilizing sterols in symmetric vesicles in which the ranking was cholesterol > lanosterol ~ desmosterol ~ epicholesterol or prior studies in which the ranking was cholesterol ~ epicholesterol > lanosterol ~ desmosterol. The reasons for these differences are discussed. Based on these results, we re-evaluated our prior studies in cells and conclude that endocytosis levels and bacterial uptake are even more closely correlated with the ability of sterols to form ordered domains than previously thought, and do not necessarily require that a sterol have a 3β-OH group.     

Current LCA database development in Japan -results of the LCA project

In 1998, the Japan’s Ministry of Economy, Trade, and Industry (METI) launched a five-year national project entitled ‘Development of Life Cycle Impact Assessment for Products’ (commonly known as ‘the LCA Project’). The purpose of the project is to develop common LCA methodology as well as a highly reliable database that can be shared in Japan. Activities over these five years have resulted in the supply of LCI data on some 250 products. Industrial associations voluntarily provided data. The results of these activities are currently being made available on the Internet on a trial basis in the form of an LCA database. In addition, a method entitled ‘Life-cycle Impact assessment Method based on Endpoint modeling (LIME)’ was developed. It is expected that these results will be widely used in Japan in the future. This paper presents an outline of the results of the research and development that has been conducted in the LCA Project in Japan.     

骨骼肌损伤修复的生理生化机制研究

为探讨新西兰兔股四头肌损伤修复过程中,按摩对骨骼肌和运动终板(MEP)损伤修复的生理生化机制,将30只雄性新西兰大白兔随机分成正常组、自然恢复组(损伤后7d(3只)、14 d和21 d三个亚组(各6只))和按摩治疗组(按摩7d和14d两个亚组(各6只)).重物打击法制作兔股四头肌急性损伤模型,H&E染色,AchE酶组化...     

Implantation of Radiotelemetry Transmitters Yielding Data on ECG, Heart Rate, Core Body Temperature and Activity in Free-moving Laboratory Mice

The laboratory mouse is the animal species of choice for most biomedical research, in both the academic sphere and the pharmaceutical industry. Mice are a manageable size and relatively easy to house. These factors, together with the availability of a wealth of spontaneous and experimentally induced mutants, make laboratory mice ideally suited to a wide variety of research areas.In cardiovascular, pharmacological and toxicological research, accurate measurement of parameters relating to the circulatory system of laboratory animals is often required. Determination of heart rate, heart rate variability, and duration of PQ and QT intervals are based on electrocardiogram (ECG) recordings. However, obtaining reliable ECG curves as well as physiological data such as core body temperature in mice can be difficult using conventional measurement techniques, which require connecting sensors and lead wires to a restrained, tethered, or even anaesthetized animal. Data obtained in this fashion must be interpreted with caution, as it is well known that restraining and anesthesia can have a major artifactual influence on physiological parameters^{1, 2}.Radiotelemetry enables data to be collected from conscious and untethered animals. Measurements can be conducted even in freely moving animals, and without requiring the investigator to be in the proximity of the animal. Thus, known sources of artifacts are avoided, and accurate and reliable measurements are assured. This methodology also reduces interanimal variability, thus reducing the number of animals used, rendering this technology the most humane method of monitoring physiological parameters in laboratory animals^{3, 4}. Constant advancements in data acquisition technology and implant miniaturization mean that it is now possible to record physiological parameters and locomotor activity continuously and in realtime over longer periods such as hours, days or even weeks^{3, 5}.Here, we describe a surgical technique for implantation of a commercially available telemetry transmitter used for continuous measurements of core body temperature, locomotor activity and biopotential (i.e. onelead ECG), from which heart rate, heart rate variability, and PQ and QT intervals can be established in freeroaming, untethered mice. We also present pre-operative procedures and protocols for post-operative intensive care and pain treatment that improve recovery, well-being and survival rates in implanted mice^{5, 6}.     

Clinical and biomarker endpoint analysis in neoadjuvant endocrine therapy trials

Neoadjuvant endocrine therapy trials for breast cancer are now a widely accepted investigational approach for oncology cooperative group and pharmaceutical company research programs. However, there remains considerable uncertainty regarding the most suitable endpoints for these studies, in part, because short-term clinical, radiological or biomarker responses have not been fully validated as surrogate endpoints that closely relate to long-term breast cancer outcome. This shortcoming must be addressed before neoadjuvant endocrine treatment can be used as a triage strategy designed to identify patients with endocrine therapy “curable” disease. In this summary, information from published studies is used as a basis to critique clinical trial designs and to suggest experimental endpoints for future validation studies. Three aspects of neoadjuvant endocrine therapy designs are considered: the determination of response; the assessment of surgical outcomes; and biomarker endpoint analysis. Data from the letrozole 024 (LET 024) trial that compared letrozole and tamoxifen is used to illustrate a combined endpoint analysis that integrates both clinical and biomarker information. In addition, the concept of a “cell cycle response” is explored as a simple post-treatment endpoint based on Ki67 analysis that might have properties similar to the pathological complete response endpoint used in neoadjuvant chemotherapy trials.     

A bayesian approach to improved estimation of causal effect predictiveness for a principal surrogate endpoint

Summary The literature on potential outcomes has shown that traditional methods for characterizing surrogate endpoints in clinical trials based only on observed quantities can fail to capture causal relationships between treatments, surrogates, and outcomes. Building on the potential-outcomes formulation of a principal surrogate, we introduce a Bayesian method to estimate the causal effect predictiveness (CEP) surface and quantify a candidate surrogate's utility for reliably predicting clinical outcomes. In considering the full joint distribution of all potentially observable quantities, our Bayesian approach has the following features. First, our approach illuminates implicit assumptions embedded in previously-used estimation strategies that have been shown to result in poor performance. Second, our approach provides tools for making explicit and scientifically-interpretable assumptions regarding associations about which observed data are not informative. Through simulations based on an HIV vaccine trial, we found that the Bayesian approach can produce estimates of the CEP surface with improved performance compared to previous methods. Third, our approach can extend principal-surrogate estimation beyond the previously considered setting of a vaccine trial where the candidate surrogate is constant in one arm of the study. We illustrate this extension through an application to an AIDS therapy trial where the candidate surrogate varies in both treatment arms.     

Finding A Niche for Soil Microbial Toxicity Tests in Ecological Risk Assessment

Soil microbial toxicity tests are seldom used in ecological risk assessments or in the development of regulatory criteria in the U.S. The primary reason is the lack of an explicit connection between these tests and assessment end-points. Soil microorganisms have three potential roles with respect to ecological assessment endpoints: properties of microbial communities may be end-points; microbial responses may be used to estimate effects on plant production; and microbial responses may be used as surrogates for responses of higher organisms. Rates of microbial processes are important to ecosystem function, and thus should be valued by regulatory agencies. However, the definition of the microbial assessment endpoint is often an impediment to its use in risk assessment. Decreases in rates are not always undesirable. Processes in a nutrient cycle are particularly difficult to define as endpoints, because what constitutes an adverse effect on a process is dependent on the rates of others. Microbial tests may be used as evidence in an assessment of plant production, but the dependence of plants on microbial processes is rarely considered. As assessment endpoints are better defined in the future, microbial ecologists and toxicologists should be provided with more direction for developing appropriate microbial tests.     

On testing simultaneously non-inferiority in two multiple primary endpoints and superiority in at least one of them

In a clinical trial with an active treatment and a placebo the situation may occur that two (or even more) primary endpoints may be necessary to describe the active treatment's benefit. The focus of our interest is a more specific situation with two primary endpoints in which superiority in one of them would suffice given that non-inferiority is observed in the other. Several proposals exist in the literature for dealing with this or similar problems, but prove insufficient or inadequate at a closer look (e.g. Bloch et al. (2001, 2006) or Tamhane and Logan (2002, 2004)). For example, we were unable to find a good reason why a bootstrap p-value for superiority should depend on the initially selected non-inferiority margins or on the initially selected type I error alpha. We propose a hierarchical three step procedure, where non-inferiority in both variables must be proven in the first step, superiority has to be shown by a bivariate test (e.g. Holm (1979), O'Brien (1984), Hochberg (1988), a bootstrap (Wang (1998)), or L?uter (1996)) in the second step, and then superiority in at least one variable has to be verified in the third step by a corresponding univariate test. All statistical tests are performed at the same one-sided significance level alpha. From the above mentioned bivariate superiority tests we preferred L?uter's SS test and the Holm procedure for the reason that these have been proven to control the type I error strictly, irrespective of the correlation structure among the primary variables and the sample size applied. A simulation study reveals that the performance regarding power of the bivariate test depends to a considerable degree on the correlation and on the magnitude of the expected effects of the two primary endpoints. Therefore, the recommendation of which test to choose depends on knowledge of the possible correlation between the two primary endpoints. In general, L?uter's SS procedure in step 2 shows the best overall properties, whereas Holm's procedure shows an advantage if both a positive correlation between the two variables and a considerable difference between their standardized effect sizes can be expected.