A Double‐threshold GARCH Model for the French Franc/Deutschmark exchange rate

This paper combines and generalizes a number of recent time series models of daily exchange rate series by using a SETAR model which also allows the variance equation of a GARCH specification for the error terms to be drawn from more than one regime. An application of the model to the French Franc/Deutschmark exchange rate demonstrates that out‐of‐sample forecasts for the exchange rate volatility are also improved when the restriction that the data it is drawn from a single regime is removed. This result highlights the importance of considering both types of regime shift (i.e. thresholds in variance as well as in mean) when analysing financial time series. Copyright © 2000 John Wiley & Sons, Ltd.     

Lgl, Pins and aPKC regulate neuroblast self-renewal versus differentiation

How a cell chooses to proliferate or to differentiate is an important issue in stem cell and cancer biology. Drosophila neuroblasts undergo self-renewal with every cell division, producing another neuroblast and a differentiating daughter cell, but the mechanisms controlling the self-renewal/differentiation decision are poorly understood. Here we tested whether cell polarity genes, known to regulate embryonic neuroblast asymmetric cell division, also regulate neuroblast self-renewal. Clonal analysis in larval brains showed that pins mutant neuroblasts rapidly fail to self-renew, whereas lethal giant larvae (lgl) mutant neuroblasts generate multiple neuroblasts. Notably, lgl pins double mutant neuroblasts all divide symmetrically to self-renew, filling the brain with neuroblasts at the expense of neurons. The lgl pins neuroblasts show ectopic cortical localization of atypical protein kinase C (aPKC), and a decrease in aPKC expression reduces neuroblast numbers, suggesting that aPKC promotes neuroblast self-renewal. In support of this hypothesis, neuroblast-specific overexpression of membrane-targeted aPKC, but not a kinase-dead version, induces ectopic neuroblast self-renewal. We conclude that cortical aPKC kinase activity is a potent inducer of neuroblast self-renewal.     

Single kinesin molecules studied with a molecular force clamp.

Kinesin is a two-headed, ATP-driven motor protein that moves processively along microtubules in discrete steps of 8 nm, probably by advancing each of its heads alternately in sequence. Molecular details of how the chemical energy stored in ATP is coupled to mechanical displacement remain obscure. To shed light on this question, a force clamp was constructed, based on a feedback-driven optical trap capable of maintaining constant loads on single kinesin motors. The instrument provides unprecedented resolution of molecular motion and permits mechanochemical studies under controlled external loads. Analysis of records of kinesin motion under variable ATP concentrations and loads revealed several new features. First, kinesin stepping appears to be tightly coupled to ATP hydrolysis over a wide range of forces, with a single hydrolysis per 8-nm mechanical advance. Second, the kinesin stall force depends on the ATP concentration. Third, increased loads reduce the maximum velocity as expected, but also raise the apparent Michaelis-Menten constant. The kinesin cycle therefore contains at least one load-dependent transition affecting the rate at which ATP molecules bind and subsequently commit to hydrolysis. It is likely that at least one other load-dependent rate exists, affecting turnover number. Together, these findings will necessitate revisions to our understanding of how kinesin motors function.     

对氨基苯甲酸(PABA)的生物合成及酶功能的相互影响

由莽草酸经分枝酸进行的生物合成有五个反应途径，其中最复杂的是对氨基苯甲酸（PABA）的合成，反应涉及到三个酶PabA、PabB和PabC。利用提纯的酶于实验里再现了生物体内的这一合成过程，在λ=265nm对酶的活性进行了连续的测定,经核磁共振确定了产物为PABA。在对底物作用中，PabB和PabC二聚体的形成对PABA的生物合成过程十分重要，它加速了PABA从PabB上的解离速度。当所加入的PabB和PabC的浓度比趋于1∶1时，PABA的生成速率趋于最大。     

酶的硫酸铵沉淀浓度范围的确定

采用分步边疆沉淀酶方法，确定硫酸铵沉淀饱和百分数范围，在一只离心管中完成整个实验，避免了溶液转移以及计算与实际操作不一致带来的误差，并以上清液取样代替直接测定沉淀中含量，消除了沉淀不能与溶液彻底分净引起的误差，实验中测定了生物合成对＝氨基苯甲酸的氨基脱氧分枝酸合成酶和氨基脱氧分枝酸裂解酶的硫酸铵沉淀的饱和百分数,辚20％到70％和25％到55％，而最佳的提纯百分浓度范围为25％到50％和25％到45％。     

Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans

Theories of instrumental learning are centred on understanding how success and failure are used to improve future decisions. These theories highlight a central role for reward prediction errors in updating the values associated with available actions. In animals, substantial evidence indicates that the neurotransmitter dopamine might have a key function in this type of learning, through its ability to modulate cortico-striatal synaptic efficacy. However, no direct evidence links dopamine, striatal activity and behavioural choice in humans. Here we show that, during instrumental learning, the magnitude of reward prediction error expressed in the striatum is modulated by the administration of drugs enhancing (3,4-dihydroxy-L-phenylalanine; L-DOPA) or reducing (haloperidol) dopaminergic function. Accordingly, subjects treated with L-DOPA have a greater propensity to choose the most rewarding action relative to subjects treated with haloperidol. Furthermore, incorporating the magnitude of the prediction errors into a standard action-value learning algorithm accurately reproduced subjects' behavioural choices under the different drug conditions. We conclude that dopamine-dependent modulation of striatal activity can account for how the human brain uses reward prediction errors to improve future decisions.