Pharmaco-metabonomic phenotyping and personalized drug treatment

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.     

Positive and negative effects of widespread badger culling on tuberculosis in cattle

Human and livestock diseases can be difficult to control where infection persists in wildlife populations. For three decades, European badgers (Meles meles) have been culled by the British government in a series of attempts to limit the spread of Mycobacterium bovis, the causative agent of bovine tuberculosis (TB), to cattle. Despite these efforts, the incidence of TB in cattle has risen consistently, re-emerging as a primary concern for Britain's cattle industry. Recently, badger culling has attracted controversy because experimental studies have reached contrasting conclusions (albeit using different protocols), with culled areas showing either markedly reduced or increased incidence of TB in cattle. This has confused attempts to develop a science-based management policy. Here we use data from a large-scale, randomized field experiment to help resolve these apparent differences. We show that, as carried out in this experiment, culling reduces cattle TB incidence in the areas that are culled, but increases incidence in adjoining areas. These findings are biologically consistent with previous studies but will present challenges for policy development.     

A new gamma-ray burst classification scheme from GRB 060614

Gamma-ray bursts (GRBs) are known to come in two duration classes, separated at approximately 2 s. Long-duration bursts originate from star-forming regions in galaxies, have accompanying supernovae when these are near enough to observe and are probably caused by massive-star collapsars. Recent observations show that short-duration bursts originate in regions within their host galaxies that have lower star-formation rates, consistent with binary neutron star or neutron star-black hole mergers. Moreover, although their hosts are predominantly nearby galaxies, no supernovae have been so far associated with short-duration GRBs. Here we report that the bright, nearby GRB 060614 does not fit into either class. Its approximately 102-s duration groups it with long-duration GRBs, while its temporal lag and peak luminosity fall entirely within the short-duration GRB subclass. Moreover, very deep optical observations exclude an accompanying supernova, similar to short-duration GRBs. This combination of a long-duration event without an accompanying supernova poses a challenge to both the collapsar and the merging-neutron-star interpretations and opens the door to a new GRB classification scheme that straddles both long- and short-duration bursts.     

Southern Ocean sea-ice extent, productivity and iron flux over the past eight glacial cycles

Sea ice and dust flux increased greatly in the Southern Ocean during the last glacial period. Palaeorecords provide contradictory evidence about marine productivity in this region, but beyond one glacial cycle, data were sparse. Here we present continuous chemical proxy data spanning the last eight glacial cycles (740,000 years) from the Dome C Antarctic ice core. These data constrain winter sea-ice extent in the Indian Ocean, Southern Ocean biogenic productivity and Patagonian climatic conditions. We found that maximum sea-ice extent is closely tied to Antarctic temperature on multi-millennial timescales, but less so on shorter timescales. Biological dimethylsulphide emissions south of the polar front seem to have changed little with climate, suggesting that sulphur compounds were not active in climate regulation. We observe large glacial-interglacial contrasts in iron deposition, which we infer reflects strongly changing Patagonian conditions. During glacial terminations, changes in Patagonia apparently preceded sea-ice reduction, indicating that multiple mechanisms may be responsible for different phases of CO2 increase during glacial terminations. We observe no changes in internal climatic feedbacks that could have caused the change in amplitude of Antarctic temperature variations observed 440,000 years ago.     

Editing-defective tRNA synthetase causes protein misfolding and neurodegeneration

Misfolded proteins are associated with several pathological conditions including neurodegeneration. Although some of these abnormally folded proteins result from mutations in genes encoding disease-associated proteins (for example, repeat-expansion diseases), more general mechanisms that lead to misfolded proteins in neurons remain largely unknown. Here we demonstrate that low levels of mischarged transfer RNAs (tRNAs) can lead to an intracellular accumulation of misfolded proteins in neurons. These accumulations are accompanied by upregulation of cytoplasmic protein chaperones and by induction of the unfolded protein response. We report that the mouse sticky mutation, which causes cerebellar Purkinje cell loss and ataxia, is a missense mutation in the editing domain of the alanyl-tRNA synthetase gene that compromises the proofreading activity of this enzyme during aminoacylation of tRNAs. These findings demonstrate that disruption of translational fidelity in terminally differentiated neurons leads to the accumulation of misfolded proteins and cell death, and provide a novel mechanism underlying neurodegeneration.     

Thermal radiation scanning tunnelling microscopy

In standard near-field scanning optical microscopy (NSOM), a subwavelength probe acts as an optical 'stethoscope' to map the near field produced at the sample surface by external illumination. This technique has been applied using visible, infrared, terahertz and gigahertz radiation to illuminate the sample, providing a resolution well beyond the diffraction limit. NSOM is well suited to study surface waves such as surface plasmons or surface-phonon polaritons. Using an aperture NSOM with visible laser illumination, a near-field interference pattern around a corral structure has been observed, whose features were similar to the scanning tunnelling microscope image of the electronic waves in a quantum corral. Here we describe an infrared NSOM that operates without any external illumination: it is a near-field analogue of a night-vision camera, making use of the thermal infrared evanescent fields emitted by the surface, and behaves as an optical scanning tunnelling microscope. We therefore term this instrument a 'thermal radiation scanning tunnelling microscope' (TRSTM). We show the first TRSTM images of thermally excited surface plasmons, and demonstrate spatial coherence effects in near-field thermal emission.     

Cortical substrates for exploratory decisions in humans

Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration-exploitation' dilemma, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.     

多层弹道导弹防御体系火力分配模型求解算法研究

研究了多层弹道导弹防御体系火力分配问题。首先对多层弹道导弹防御体系火力分配问题进行了描述;其次建立了基于最大化资源剩余价值目标函数的多层弹道导弹防御体系火力分配模型;多层弹道导弹防御体系火力分配模型是非线性NP难问题,针对目标函数的特点,应用线性逼近的方法,建立了易于求解的多层弹道导弹防御体系火力分配模型的近似线性规划模型;最后针对具体实例,应用多层弹道导弹防御体系火力分配线性规划模型,采用分之定界算法进行求解,仿真结果验证了模型的有效性及实时性。     

近52 a湖北省雷暴气候特征及其变化研究

为进一步研究湖北雷暴气候及其时空变化规律,利用1961年～2012年近52年湖北省68个气象台站雷暴日资料,采用小波分析和EOF等数理统计方法,对湖北地区雷暴日数时空分布特征及其变化规律进行了分析研究.结果表明：近52年湖北年平均雷暴日数在波动中总体呈明显下降趋势,东亚夏季风强弱与夏季雷暴日数多少相关性显著,初步认为东亚夏季风减弱是夏季和年雷暴日数减少的主要原因.湖北年平均雷暴日数为20～53 d,平均为36 d.平均初雷日期在2月28日,并在波动中有弱的推迟趋势;平均终雷日期在10月6日或7日,在波动中没有提前或推迟趋势.月平均雷暴日数变化呈双峰型,主峰在7月,次峰在4月,7～8月雷暴日数较多,占全年雷暴日数的47.2%.5～9月各月平均雷暴日数减少趋势显著,8月平均雷暴日数减少最显著.春、夏、秋、冬四个季节雷暴日数分别占全年雷暴日数的29.2%、59.2%、8.2%和3.4%,春夏季平均雷暴日数占全年雷暴日数的88.4%.鄂西北和江汉平原年平均雷暴日数较少,鄂西南、鄂东南和鄂东北年平均雷暴日数较多.地形对终雷日期、夏季和年平均雷暴日数影响明显,同纬度地区,山区雷暴日数比平原多.经M-K法检验,1984年是年平均雷暴日数明显减少的气候突变年份,通过小波分析,年平均雷暴日数变化主要存在着11 a、18 a左右长周期和3－5a小周期振荡,目前湖北年平均雷暴日数正处于偏少期的中后期阶段.根据EOF分析,将湖北年平均雷暴日空间分布划分为一致型、反相型和局地型3种类型.依据国家相关标准,将湖北地区划分为多雷区、中雷区和少雷区三个雷暴等级.