Thinking about biology and culture: can the natural and human sciences be integrated?

Genomic analyses have shown that only 1.2 per cent of the genome is devoted to protein coding sequences (the most commonly invoked definition of genes), and that much of the remaining sequences are employed in regulation – that is, in responding to signals, first, from the immediate environment of the DNA, but ultimately from the distal environment – from the cytoplasm, from the environment outside the cell, and finally, from the environment beyond the organism. Such signals are not restricted to the simple physical and chemical stimuli that impinge directly on the DNA, on the surface of the cell, or even on the body as a whole: organisms with central nervous systems have receptors for forms of perception that are not only more complex but far longer range. Humans have especially sophisticated perceptual capacities, enabling them to respond to a wide range of complex visual, auditory, linguistic and behavioural/emotional signals in their extended environment. Research has recently begun to show that responses to such signals can extend all the way down to the level of gene expression. The question is this: to what extent are we witnessing (at last) a rapprochement between the natural science of biology and the human sciences of sociology and anthropology, and to what extent do the new promises of synthesis merely reflect an expansion of older reductionist aims, threatening once again to marginalize rather than incorporate the insights of cultural analysis? As in my earlier discussion of the nature/nurture debate (2010), my focus will be restricted to the Anglo-American context.     

How biology became social,and what it means for social theory

In this paper I first offer a systematic outline of a series of conceptual novelties in the life‐sciences that have favoured, over the last three decades, the emergence of a more social view of biology. I focus in particular on three areas of investigation: (1) technical changes in evolutionary literature that have provoked a rethinking of the possibility of altruism, morality and prosocial behaviours in evolution; (2) changes in neuroscience, from an understanding of the brain as an isolated data processor to the ultrasocial and multiply connected social brain of contemporary neuroscience; and (3) changes in molecular biology, from the view of the gene as an autonomous master of development to the ‘reactive genome’ of the new emerging field of molecular epigenetics. In the second section I reflect on the possible implications for the social sciences of this novel biosocial terrain and argue that the postgenomic language of extended epigenetic inheritance and blurring of the nature/nurture boundaries will be as provocative for neo‐Darwinism as it is for the social sciences as we have known them. Signs of a new biosocial language are emerging in several social‐science disciplines and this may represent an exciting theoretical novelty for twenty‐first social theory.     

The potential of integrated modelling in conservation biology: A case study of the black‐footed albatross (Phoebastria nigripes)

Conservation biology aims at assessing the status of a population, based on information which is often incomplete. Integrated population modelling based on state‐space models appears to be a powerful and relevant way of combining into a single likelihood several types of information such as capture‐recapture data and population surveys. In this paper, the authors describe the principles of integrated population modelling and they evaluate its performance for conservation biology based on a case study, that of the black‐footed albatross, a northern Pacific albatross species suspected to be impacted by longline fishing     

Bayesian inference for a discretely observed stochastic kinetic model

The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observed by means of discrete-time sampling systems, which are often limited in their completeness. In this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes behaviour typical of many biochemical networks which exhibit auto-regulatory behaviour. Various MCMC algorithms are described and their performance evaluated in several data-poor scenarios. An algorithm based on an approximating process is shown to be particularly efficient.     

我的生物学哲学研究——在普遍性与特异性之间的两极张力

生物学哲学的特异性主要表现在单纯还原论的失效、存在弱定律、目的论说明升值等.然而科学哲学的通用原理仍然有效,因而在特异性与普遍性之间应保持必要的张力.系统科学是生物学的元理论,互补策略是最好的启发原则.这些新现点在生物学哲学研究方面有一定代表性.     

Stochasticity in Physiologically Based Kinetics Models: Implications for Cancer Risk Assessment

In case of low-dose exposure to a substance, its concentration in cells is likely to be stochastic. Assessing the consequences of this stochasticity in toxicological risk assessment requires the coupling of macroscopic dynamics models describing whole-body kinetics with microscopic tools designed to simulate stochasticity. In this article, we propose an approach to approximate stochastic cell concentration of butadiene in the cells of diverse organs. We adapted the dynamics equations of a physiologically based pharmacokinetic (PBPK) model and used a stochastic simulator for the system of equations that we derived. We then coupled kinetics simulations with a deterministic hockey stick model of carcinogenicity. Stochasticity induced substantial modifications relative to dose-response curve, compared with the deterministic situation. In particular, there was nonlinearity in the response and the stochastic apparent threshold was lower than the deterministic one. The approach that we developed could easily be extended to other biological studies to assess the influence of stochasticity at macroscopic scale for compound dynamics at the cell level.     

New combinatorial structures with applications to efficient group testing with inhibitors

Group testing with inhibitors (GTI) is a variant of classical group testing where in addition to positive items and negative items, there is a third class of items called inhibitors. In this model the response to a test is YES if and only if the tested group of items contains at least one positive item and no inhibitor. This model of group testing has been introduced by Farach et al. (Proceedings of compression and complexity of sequences, pp 357–367, 1997) for applications in the field of molecular biology. In this paper we investigate the GTI problem both in the case when the exact number of positive items is given, and in the case when the number of positives is not given but we are provided with an upper bound on it. For the latter case, we present a lower bound on the number of tests required to determine the positive items in a completely nonadaptive fashion. Also under the same hypothesis, we derive an improved lower bound on the number of tests required by any algorithm (using any number of stages) for the GTI problem. As far as it concerns the case when the exact number of positives is known, we give an efficient trivial two-stage algorithm. Instrumental to our results are new combinatorial structures introduced in this paper. In particular we introduce generalized versions of the well known superimposed codes (Du, D.Z., Hwang, F.K. in Pooling designs and nonadaptive group testing, 2006; Dyachkov, A.G., Rykov, V.V. in Probl. Control Inf. Theory 12:7–13, 1983; Dyachkov, A.G., et al. in J. Comb. Theory Ser. A 99:195–218, 2002; Kautz, W.H., Singleton, R.R. in IEEE Trans. Inf. Theory 10:363–377, 1964) and selectors (Clementi, A.E.F, et al. in Proceedings of symposium on discrete algorithms, pp. 709–718, 2001; De Bonis, A., et al. in SIAM J Comput. 34(5):1253–1270, 2005; Indyk, P. in Proceedings of symposium on discrete algorithms, pp. 697–704, 2002) that we believe to be of independent interest.     

医学发育生物学教学模式探讨

医学发育生物学是随着生命科学领域各学科的发展，尤其是发育生物学和医学的发展而逐渐建立起来的一门新型学科。文章就医学发育生物学的发展、与其他相关学科的关联以及教学模式进行初步探讨，期望能为医学发育生物学课程的进一步优化提供一些有益的信息。     

铬对海洋生物的影响

铬(Cr)是生物代谢活动中的一个基本营养元素,又是一个很毒的重金属元素。海水中溶解态铬主要以Cr(Ⅲ)、Cr(Ⅵ)和有机铬等形态存在;铬元素在海洋生物体内分布广泛,铬对单细胞藻类有一定的毒害作用,不同种类的单细胞藻类对铬元素有不同程度的富集作用,海洋细菌可将无机铬转化为有机铬;近年来,含铬的饲料已应用于水产养殖业,海洋环境污染研究中也将铬作为监测指标之一。     

新型镧硅磷酸铝分子筛LaSAPO的合成

选用表面活性剂四甲基氢氧化铵(TMAOH)和十六烷基三甲基溴化铵(CTAB)为模板剂,采用水热晶化法合成了镧硅磷酸铝分子筛(LaSAPO),用XRD技术考察了晶化温度、晶化时间、模板剂用量、硅铝比及体系pH值等条件对分子筛晶相的形成和产物结晶度的影响.实验结果表明:适宜的合成条件为晶化时间36h;晶化温度170℃;反应混合物的pH值范围6.0~7.0.各物质最佳摩尔比为:Al2O3∶P2O5∶SiO2∶La2O3∶CTAB∶H2O∶TMAOH=1.0∶1.0∶0.6∶0.4∶0.35∶335∶3.83.