PREDICTING MICROEVOLUTIONARY RESPONSES TO DIRECTIONAL SELECTION ON HERITABLE VARIATION

Microevolution of quantitative traits in the wild can be predicted from a knowledge of selection and genetic parameters. Testing the predictions requires measurement of the offspring of the selected group, a requirement that is difficult to meet. We present the results of a study of Darwin's finches on the Galápagos island of Daphne Major where this requirement is met. The study demonstrates microevolutionary consequences of natural selection.     

Estimating ecotoxicological risk and impact using indigenous aquatic microbial communities

Emphasis has increased on accuracy in predicting the effect that anthropogenic stress has on natural ecosystems. Although toxicity tests low in environmental realism, such as standardized single species procedures, have been useful in providing a certain degree of protection to human health and the environment, the accuracy of such tests for predicting the effects of anthropogenic activities on complex ecosystems is questionable. The use of indigenous communities of microorganisms to assess the hazard of toxicants in aquatic ecosystems has many advantages. Theoretical and practical aspects of microbial community tests are discussed, particularly in related to widely cited problems in the use of multispecies test systems for predicting hazard. Further standardization of testing protocols using microbial colonization dynamics is advocated on the basis of previous studies, which have shown these parameters to be useful in assessing risk and impact of hazardous substances in aquatic ecosystems.     

Hepatocytes--the choice to investigate drug metabolism and toxicity in man: in vitro variability as a reflection of in vivo

The pharmaceutical industry is committed to marketing safer drugs with fewer side effects, predictable pharmacokinetic properties and quantifiable drug-drug interactions. Drug metabolism is a major determinant of drug clearance and interindividual pharmacokinetic differences, and an indirect determinant of the clinical efficacy and toxicity of drugs. Progressive advances in the knowledge of metabolic routes and enzymes responsible for drug biotransformation have contributed to understanding the great metabolic variations existing in human beings. Phenotypic as well genotypic differences in the expression of the enzymes involved in drug metabolism are the main causes of this variability. However, only a minor part of phenotypic variability in man is attributable to gene polymorphisms, thus making the definition of a normal liver complex. At present, the use of human in vitro hepatic models at early preclinical stages means that the process of selecting drug candidates is becoming much more rational. Cultured human hepatocytes are considered to be the closest model to human liver. However, the fact that hepatocytes are located in a microenvironment that differs from that of the cell in the liver raises the question: to what extent does drug metabolism variability observed in vitro actually reflect that of the liver in vivo? By comparing the metabolism of a model compound both in vitro and in vivo in the same individual, a good correlation between the in vitro and in vivo relative abundance of oxidized metabolites and the hydrolysis of the compound was observed. Thus, it is reasonable to consider that the variability observed in human hepatocytes reflects the existing phenotypic heterogeneity of the P450 expression in human liver.     

The pivotal role of hepatocytes in drug discovery

This review promotes the value of isolated hepatocytes in modern Drug Discovery programmes and outlines how increased understanding, particularly in the area of in vitro-in vivo extrapolation (IVIVE), has led to more widespread use. The importance of in vitro metabolic intrinsic clearance data for predicting in vivo clearance has been acknowledged for several years and the greater utility of hepatocytes, compared with hepatic microsomes and liver slices, for this application is discussed. The application of hepatocytes in predicting drug-drug interactions (DDIs) resulting from reversible and irreversible (time-dependent) inhibition is relatively novel but affords the potential to study both phase I and phase II processes together with any impact of drug efflux and/or uptake (cellular accumulation). Progress in this area is reviewed along with current opinions on the comparative use of primary hepatocytes and higher throughput reporter gene-based systems for studying cytochrome P450 (CYP) induction. The appreciation of the role of transporter proteins in drug disposition continues to evolve. The study of hepatic uptake using isolated hepatocytes and the interplay between drug transport and metabolism with respect to both clearance and DDIs and subsequent IVIVE is also considered.     

Extensive unfolding of the C-LytA choline-binding module by submicellar concentrations of sodium dodecyl sulphate

We have investigated the stability of the choline-binding module C-LytA against sodium dodecyl sulphate (SDS)-induced unfolding at pH 7.0 and 20 degrees C. A major intermediate with an unfolded N-terminal region accumulates at around 0.75 mM SDS, whereas 2.0 mM SDS was sufficient for a complete unfolding. This might be the first report of a protein being extensively unfolded by submicellar concentrations of SDS, occurring through formation of detergent clusters on the protein surface. All transitions were reversible upon SDS complexation with beta-cyclodextrin, allowing the calculation of thermodynamic parameters. A model for the unfolding of C-LytA by SDS is presented and compared to a previous denaturation scheme by guanidine hydrochloride.     

An evaluation of transferability of ecological niche models

Ecological niche modeling (ENM) is used widely to study species’ geographic distributions. ENM applications frequently involve transferring models calibrated with environmental data from one region to other regions or times that may include novel environmental conditions. When novel conditions are present, transferability implies extrapolation, whereas, in absence of such conditions, transferability is an interpolation step only. We evaluated transferability of models produced using 11 ENM algorithms from the perspective of interpolation and extrapolation in a virtual species framework. We defined fundamental niches and potential distributions of 16 virtual species distributed across Eurasia. To simulate real situations of incomplete understanding of species’ distribution or existing fundamental niche (environmental conditions suitable for the species contained in the study area; N* _F ), we divided Eurasia into six regions and used 1–5 regions for model calibration and the rest for model evaluation. The models produced with the 11 ENM algorithms were evaluated in environmental space, to complement the traditional geographic evaluation of models. None of the algorithms accurately estimated the existing fundamental niche (N* _F ) given one region in calibration, and model evaluation scores decreased as the novelty of the environments in the evaluation regions increased. Thus, we recommend quantifying environmental similarity between calibration and transfer regions prior to model transfer, providing an avenue for assessing uncertainty of model transferability. Different algorithms had different sensitivity to completeness of knowledge of N* _F , with implications for algorithm selection. If the goal is to reconstruct fundamental niches, users should choose algorithms with limited extrapolation when N* _F is well known, or choose algorithms with increased extrapolation when N* _F is poorly known. Our assessment can inform applications of ecological niche modeling transference to anticipate species invasions into novel areas, disease emergence in new regions, and forecasts of species distributions under future climate conditions.     

北京东灵山地区植物群落多样性研究 Ⅵ.几种类型植物群落物种数目的估计

采用经验贝叶斯方法、非参数方法（刀切法和自助法）和种－面积曲线外推方法对北京东灵山地区５种类型植物群落的物种数目进行了估计,考察了这些方法的估计行为,从中得出如下结论：（１）只要抽样强度不是很小,经验贝叶斯方法就能给出群落物种数目很好的估计,但与非参数方法相比,其估计的标准差较大;（２）在适当的抽样强度下,非参数方法也能给出群落物种数目很好的估计。如果抽样强度过低,则估计值也偏低;相反,如果抽样强度过高,则估计值也偏高。但在各种抽样强度下,非参数方法估计的标准差都比经验贝叶斯方法的小;（３）种－面积曲线２、３、４、５、６可以给出群落物种数目较好的估计,曲线１的估计值偏高,而曲线７、８、９、１０的估计值则偏低;（４）经过几种方法的综合比较,可以对群落１、２、３、４、５的各层及整个群落的物种数目分别做出如下估计;乔木层１６、１９、２１、１２、１６,灌木层１３、１５、２１、１４、２１,草本层４９、４６、５４、８２、５５,整个群落７９、８０、９６、１０７、９２。     

On the Definition of Internal Dose Metrics

Internal dose metrics, as computed with pharmacokinetic models, are increasingly used as a means for extrapolating animal toxicological data to humans and to extrapolate across routes of administration. These internal dose metrics are thought to provide a more scientific means of comparing toxicological effects across animal species. The use of internal dose metrics is based on the universal assumption that toxic effects are equal across species if and only if the concentration of the toxic moieties in the target tissue is equal across species. Herein it is shown that this assumption is inconsistent with empirical toxicological data. It is shown that measurement of internal dose metrics in chronological time, as is done for AUC (Area under the concentration curve) and rate of metabolite production per kg of target tissue, does not produce equal toxic effects across species. A consequence of this observation is that the application of pharmacokinetics in risk assessments for such important chemicals as trichloroethylene, vinyl chloride, perchloroethylene, and perchlorate may need reassessment.     

Multiplicity-adjusted inferences in risk assessment: benchmark analysis with quantal response data

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases data are not available at low doses or low exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this short note, we discuss approaches for doing so with quantal response data.     

The regulatory factor SipA is a highly stable β-II class protein with a SH3 fold

The small regulator SipA, interacts with the ATP-binding domain of non-bleaching sensor histidine kinase (NblS), the most conserved histidine kinase in cyanobacteria. NblS regulates photosynthesis and acclimation to a variety of environmental conditions. We show here that SipA is a highly stable protein in a wide pH range, with a thermal denaturation midpoint of 345 K. Circular dichroism and 1D ¹H NMR spectroscopies, as well as modelling, suggest that SipA is a β-II class protein, with short strands followed by turns and long random-coil polypeptide patches, matching the SH3 fold. The experimentally determined m-value and the heat capacity change upon thermal unfolding (ΔC_p) closely agreed with the corresponding theoretical values predicted from the structural model, further supporting its accuracy.