改进生物化学实验教学模式,培养学生综合能力

为适应现代医学教育的发展,加强学生能力的培养,提高学生综合素质,对生物化学实验内容和教学形式进行了改革,在实验内容上设置了综合性实验;在教学方法上注重突出学生的主体作用,学生主动参与实验设计、实验讨论、实验方案的确定,独立完成实验过程的教学形式.实践证明,新的教学模式达到了预期的教学效果,有推广价值.     

Upper bound estimators of the population size based on ordinal models for capture‐recapture experiments

Capture‐recapture studies have attracted a lot of attention over the past few decades, especially in applied disciplines where a direct estimate for the size of a population of interest is not available. Epidemiology, ecology, public health, and biodiversity are just a few examples. The estimation of the number of unseen units has been a challenge for theoretical statisticians, and considerable progress has been made in providing lower bound estimators for the population size. In fact, it is well known that consistent estimators for this cannot be provided in the very general case. Considering a case where capture‐recapture studies are summarized by a frequency of frequencies distribution, we derive a simple upper bound of the population size based on the cumulative distribution function. We introduce two estimators of this bound, without any specific parametric assumption on the distribution of the observed frequency counts. The behavior of the proposed estimators is investigated using several benchmark datasets and a large‐scale simulation experiment based on the scheme discussed by Pledger.     

Field and microcosm experiments to evaluate the effects of agricultural Cu treatment on the density and genetic structure of microbial communities in two different soils

The effects of Cu amendment on indigenous soil microorganisms were investigated in two soils, a calcareous silty clay (Ep) and a sandy soil (Au), by means of a 1-year field experiment and a two-month microcosm incubation. Cu was added as 'Bordeaux mixture' [CuSO(4), Ca(OH)(2)] at the standard rate used in viticulture (B1=16 kg Cu kg(-1) soil) and at a higher level of contamination (B3=48 kg Cu ha(-1) soil). More extractable Cu was observed in sandy soil (Au) than in silty soil (Ep). Furthermore, total Cu and Cu-EDTA declined with time in Au soil, whereas they remained stable in Ep soil. Quantitative modifications of the microflora were assessed by C-biomass measurements and qualitative modifications were assessed by the characterization of the genetic structure of bacterial and fungal communities from DNA directly extracted from the soil, using B- and F-ARISA (bacterial and fungal automated ribosomal intergenic spacer analysis). In the field study, no significant modifications were observed in C-biomass whereas microcosm incubation showed a decrease in B3 contamination only. ARISA fingerprinting showed slight but significant modifications of bacterial and fungal communities in field and microcosm incubation. These modifications were transient in all cases, suggesting a short-term effect of Cu stress. Microcosm experiments detected the microbial community modifications with greater precision in the short-term, while field experiments showed that the biological effects of Cu contamination may be overcome or hidden by pedo-climatic variations.     

A Laplace mixture model for identification of differential expression in microarray experiments

Microarrays have become an important tool for studying the molecular basis of complex disease traits and fundamental biological processes. A common purpose of microarray experiments is the detection of genes that are differentially expressed under two conditions, such as treatment versus control or wild type versus knockout. We introduce a Laplace mixture model as a long-tailed alternative to the normal distribution when identifying differentially expressed genes in microarray experiments, and provide an extension to asymmetric over- or underexpression. This model permits greater flexibility than models in current use as it has the potential, at least with sufficient data, to accommodate both whole genome and restricted coverage arrays. We also propose likelihood approaches to hyperparameter estimation which are equally applicable in the Normal mixture case. The Laplace model appears to give some improvement in fit to data, though simulation studies show that our method performs similarly to several other statistical approaches to the problem of identification of differential expression.     

Variation in rocky shore assemblages in the northwestern Mediterranean: contrasts between islands and the mainland

Insular assemblages of species are often considered unique because they are exposed to unpredictable patterns of colonization/extinction that depend on distance from other sources of colonists and on size of islands. An alternative explanation is that islands provide fundamentally different habitats of those of the mainland, regardless of any possible effect of size and isolation. These alternatives were examined by comparing assemblages of rocky shores on islands of the Tuscany Archipelago with those of the mainland in the same geographical region. Sandy beaches created a pattern of discrete areas of rock along the mainland with spatial discontinuities and extents comparable to those of the insular environment. Possible effects of isolation and size were therefore controlled in this study, so that one would expect no difference between islands and the mainland if only size and isolation matter. In contrast, differences are expected if historical events or other processes have distinct influences on assemblages in these environments. These hypotheses were tested by comparing assemblages of midshore and lowshore habitats of two islands with those of two similarly distributed locations on the mainland over a period of 2 years, using a hierarchical sampling design. Multivariate and univariate analyses revealed various patterns in the data. There were differences between islands and the mainland in structure of assemblages, in mean abundance of common taxa and in the magnitude of spatial and temporal variance in abundance in both habitats. Collectively, these findings support the model that islands in the Tuscany Archipelago have distinct assemblages from the mainland, thereby contributing to the regional diversity and complexity of assemblages of rocky shores over and above any possible effect of size or isolation.     

On the Estimation of the Nearest Neighbour Distribution,G(t), for Point Processes

A new method is proposed for estimating G(t), the distribution function of the distance from an object to its nearest neighbour in a spatial point process. The new method makes more complete use of the information available and has a smaller mean squared error than that of the existing alternatives. The method appears equally effective with random, clustered and regular patterns.     

On the statistical analysis of multiple-choice feeding preference experiments

A stopping rule for an experiment defines when (under what conditions) the experiment is terminated. I investigated the stopping rules used in numerous multiple–choice feeding-preference experiments and also examined a recently proposed method for analyzing the data arising from such experiments. All of the surveyed experiments imposed stopping rules which result in a random total food consumption. If an acceptable quantification of preference is relative consumption of different food types, then the proposed analysis will likely misstate the information about preference conveyed by the data. This is due to the fact that the method may confound differences in preferences among food types with differences in the total consumption across trials. I discuss this issue in detail and present an alternative procedure which is appropriate under all stopping regimes when preference is quantified through relative consumption. The procedure I suggest uses an index which is a multivariate generalization of the preference index suggested by Kogan and Goeden (Ann Entomol Soc 1970; 63: 1175–1180) and Kogan (Ann Entomol Soc 1972; 65: 675–683) and which is analogous to a selection index for discrete food units proposed by Manly (Biometrics 1974; 30: 281–294). Received: 29 November 1997 / Accepted: 20 April 1998     

生物化学验证性实验与设计性实验结合教学的实践

为了加强本科生的综合素质和实验技能培养,对生物化学实验课进行了教学改革,采用基础实验与设计性实验相结合的教学方法。设计性实验要求加强老师的指导作用,并充分发挥学生的主体性。实践证明这种教学模式充分调动了学生的学习主动性,提高了实验操作技能和创新思维的能力;同时,通过文献查阅及对实验困难问题的解决,更好地巩固了理论知识。     

Spatial aggregation and association in different resource-patch distributions: experimental analysis with Drosophila

1. Laboratory experiments using homogeneous resources were conducted to examine intra- and interspecific spatial egg distribution of D. simulans, D. auraria and D. immigrans in three different resource-patch distribution patterns: patchy, even and clustered. 2. Individuals of each species were introduced separately or simultaneously into the cage, into which artificial substrates were placed and allowed to oviposit for 24 h. Spatial analyses were performed with indices of intraspecific aggregation (J), interspecific association (C) and L-function based on Ripley's K-function. 3. Eggs were always spatially aggregated irrespective of species and the resource-patch distribution patterns. Spatial egg aggregation was influenced significantly by the resource-patch distribution pattern and tended to be weaker in the clustered resource-patch distribution than in the patchy or even resource-patch distribution. 4. Spatial extent of egg aggregation was always beyond the single resource patch scale, indicating aggregation of ovipositing females. 5. Interspecific association of egg distribution was absent or very weak. Thus, these results present experimental evidence of independent egg aggregation among drosophilids.     

Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments

Systems biology applies quantitative, mechanistic modelling to study genetic networks, signal transduction pathways and metabolic networks. Mathematical models of biochemical networks can look very different. An important reason is that the purpose and application of a model are essential for the selection of the best mathematical framework. Fundamental aspects of selecting an appropriate modelling framework and a strategy for model building are discussed. Concepts and methods from system and control theory provide a sound basis for the further development of improved and dedicated computational tools for systems biology. Identification of the network components and rate constants that are most critical to the output behaviour of the system is one of the major problems raised in systems biology. Current approaches and methods of parameter sensitivity analysis and parameter estimation are reviewed. It is shown how these methods can be applied in the design of model-based experiments which iteratively yield models that are decreasingly wrong and increasingly gain predictive power.