利用不同分辨率卫星影像的NDVI数据估算叶面积指数(LAI) ——以岷江上游为例

短周期的低分辨率遥感数据为大面积估算LAI及季节动态和物候趋势提供了有利工具,但基于高分辨率LAI的遥感估算模型在低分辨率遥感数据上应用有很大的不确定性。研究利用LAI-2000冠层分析仪与跟踪辐射和冠层结构测量仪(TRAC),测定了岷江上游流域范围内490块野外调查样地（50m×50m样方）的LAI数据,结合同期较高精度卫星数据（TM）建立了不同植被类型的LAI-NDVI算法,在经过传感器的相对校正后,将这种算法应用到同期分辨率较低的MODIS数据和SPOT VEGETATION数据上。结果表明,30m 分辨率的TM LAI的均值为4.53,250m MODIS LAI的均值为3.55,1000m VGT LAI的均值为4.20,随着栅格分辨率的降低,总体标准差有增加的趋势,并且LAI值也有不同程度的低估,其中MODIS LAI值被低估约22%。但利用TM LAI数据验证MODIS 和VGT LAI数据后发现,250m的MODIS数据预测误差在30%左右,1000m的SPOT数据预测误差则高达50%,空间重采样分析表明,栅格分辨率的降低是导致预测误差扩大的主要原因,而这也是岷江流域植被分布破碎化的体现。     

利用不同分辨率卫星影像的NDVI数据估算叶面积指数(LAI)——以岷江上游为例

短周期的低分辨率遥感数据为大面积估算LAI及季节动态和物候趋势提供了有利工具,但基于高分辨率LAI的遥感估算模型在低分辨率遥感数据上应用有很大的不确定性。研究利用LAI-2000冠层分析仪与跟踪辐射和冠层结构测量仪(TRAC),测定了岷江上游流域范围内490块野外调查样地(50m×50m样方)的LAI数据,结合同期较高精度卫星数据(TM)建立了不同植被类型的LAI-NDVI算法,在经过传感器的相对校正后,将这种算法应用到同期分辨率较低的MODIS数据和SPOT VEGETATION数据上。结果表明,30m分辨率的TM LAI的均值为4.53,250m MODIS LAI的均值为3.55,1000m VGT LAI的均值为4.20,随着栅格分辨率的降低,总体标准差有增加的趋势,并且LAI值也有不同程度的低估,其中MODIS LAI值被低估约22%。但利用TM LAI数据验证MODIS和VGT LAI数据后发现,250m的MODIS数据预测误差在30%左右,1000m的SPOT数据预测误差则高达50%,空间重采样分析表明,栅格分辨率的降低是导致预测误差扩大的主要原因,而这也是岷江流域植被分布破碎化的体现。     

Correction to: Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments

Biomechanics and Modeling in Mechanobiology - In the original publication of the article, Fig. 3 and Tables 2, 4 and 5 were published with errors. The issue was caused by an error...     

Life course trajectories of systolic blood pressure using longitudinal data from eight UK cohorts

Background

Much of our understanding of the age-related progression of systolic blood pressure (SBP) comes from cross-sectional data, which do not directly capture within-individual change. We estimated life course trajectories of SBP using longitudinal data from seven population-based cohorts and one predominantly white collar occupational cohort, each from the United Kingdom and with data covering different but overlapping age periods.

Methods and Findings

Data are from 30,372 individuals and comprise 102,583 SBP observations spanning from age 7 to 80+y. Multilevel models were fitted to each cohort. Four life course phases were evident in both sexes: a rapid increase in SBP coinciding with peak adolescent growth, a more gentle increase in early adulthood, a midlife acceleration beginning in the fourth decade, and a period of deceleration in late adulthood where increases in SBP slowed and SBP eventually declined. These phases were still present, although at lower levels, after adjusting for increases in body mass index though adulthood. The deceleration and decline in old age was less evident after excluding individuals who had taken antihypertensive medication. Compared to the population-based cohorts, the occupational cohort had a lower mean SBP, a shallower annual increase in midlife, and a later midlife acceleration. The maximum sex difference was found at age 26 (+8.2 mm Hg higher in men, 95% CI: 6.7, 9.8); women then experienced steeper rises and caught up by the seventh decade.

Conclusions

Our investigation shows a general pattern of SBP progression from childhood in the UK, and suggests possible differences in this pattern during adulthood between a general population and an occupational population. Please see later in the article for the Editors'' Summary     

On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data

Knowledge of species' geographic distributions is critical for understanding and forecasting population dynamics, responses to environmental change, biodiversity patterns, and conservation planning. While many suggestive correlative occurrence models have been used to these ends, progress lies in understanding the underlying population biology that generates patterns of range dynamics. Here, we show how to use a limited quantity of demographic data to produce demographic distribution models (DDMs) using integral projection models for size‐structured populations. By modeling survival, growth, and fecundity using regression, integral projection models can interpolate across missing size data and environmental conditions to compensate for limited data. To accommodate the uncertainty associated with limited data and model assumptions, we use Bayesian models to propagate uncertainty through all stages of model development to predictions. DDMs have a number of strengths: 1) DDMs allow a mechanistic understanding of spatial occurrence patterns; 2) DDMs can predict spatial and temporal variation in local population dynamics; 3) DDMs can facilitate extrapolation under altered environmental conditions because one can evaluate the consequences for individual vital rates. To illustrate these features, we construct DDMs for an overstory perennial shrub in the Proteaceae family in the Cape Floristic Region of South Africa. We find that the species' population growth rate is limited most strongly by adult survival throughout the range and by individual growth in higher rainfall regions. While the models predict higher population growth rates in the core of the range under projected climates for 2050, they also suggest that the species faces a threat along arid range margins from the interaction of more frequent fire and drying climate. The results (and uncertainties) are helpful for prioritizing additional sampling of particular demographic parameters along these gradients to iteratively refine projections. In the appendices, we provide fully functional R code to perform all analyses.     

Computation of diagnostic data from coronary sinus pressure: a comparison between two possible models

We have evaluated two mathematical models to describe the increase in coronary sinus pressure (CSP) following pressure controlled intermittent coronary sinus occlusion (PICSO). The models are evaluated and compared on the basis of human and canine data. Both models were fitted by non-linear least squares algorithms. Next, derived quantities, such as plateau, rise-time and mean integral of the coronary sinus pressure were calculated from the model parameters. Corresponding quantities for the two models were compared with regard to mean values, rate of successful calculation and specific features characterizing the human or canine case. One model was found to be superior for investigational purposes. The other model was found to be more stable in critical situations and is therefore suggested for usage in closed loop regulation of PICSO. Physiologically, the differences in mean values of the derived quantities between the two models were found to be negligible. The formal statistical significance of the differences is but a consequence of the large number of PICSO cycles analysed.     

Regressive models for risk prediction of repeated multinomial outcomes: An illustration using Health and Retirement Study data

Life expectancy is increasing in many countries and this may lead to a higher frequency of adverse health outcomes. Therefore, there is a growing demand for predicting the risk of a sequence of events based on specified factors from repeated outcomes. We proposed regressive models and a framework to predict the joint probabilities of a sequence of events for multinomial outcomes from longitudinal studies. The Markov chain is used to link marginal and sequence of conditional probabilities to predict the joint probability. Marginal and sequence of conditional probabilities are estimated using marginal and regressive models. An application is shown using the Health and Retirement Study data. The bias of parameter estimates for all models from all bootstrap simulation is less than 1% in most of the cases. The estimated mean squared error is also very low. Results from the simulation study show negligible bias and the usefulness of the proposed model. The proposed model and framework would be useful to solve real-life problems from various fields and big data analysis.     

Value of low dose combination treatment with blood pressure lowering drugs: analysis of 354 randomised trials

Objective To determine the average reduction in blood pressure, prevalence of adverse effects, and reduction in risk of stroke and ischaemic heart disease events produced by the five main categories of blood pressure lowering drugs according to dose, singly and in combination.Design Meta-analysis of 354 randomised double blind placebo controlled trials of thiazides, β blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists, and calcium channel blockers in fixed dose.Subjects 40 000 treated patients and 16 000 patients given placebo.Main outcome measures Placebo adjusted reductions in systolic and diastolic blood pressure and prevalence of adverse effects, according to dose expressed as a multiple of the standard (recommended) doses of the drugs.Results All five categories of drug produced similar reductions in blood pressure. The average reduction was 9.1 mm Hg systolic and 5.5 mm Hg diastolic at standard dose and 7.1 mm Hg systolic and 4.4 mm Hg diastolic (20% lower) at half standard dose. The drugs reduced blood pressure from all pretreatment levels, more so from higher levels; for a 10 mm Hg higher blood pressure the reduction was 1.0 mm Hg systolic and 1.1 mm Hg diastolic greater. The blood pressure lowering effects of different categories of drugs were additive. Symptoms attributable to thiazides, β blockers, and calcium channel blockers were strongly dose related; symptoms caused by ACE inhibitors (mainly cough) were not dose related. Angiotensin II receptor antagonists caused no excess of symptoms. The prevalence of symptoms with two drugs in combination was less than additive. Adverse metabolic effects (such as changes in cholesterol or potassium) were negligible at half standard dose.Conclusions Combination low dose drug treatment increases efficacy and reduces adverse effects. From the average blood pressure in people who have strokes (150/90 mm Hg) three drugs at half standard dose are estimated to lower blood pressure by 20 mm Hg systolic and 11 mm Hg diastolic and thereby reduce the risk of stroke by 63% and ischaemic heart disease events by 46% at age 60-69.     

Blood pressure and blood flow variation during postural change from sitting to standing: model development and validation.

Short-term cardiovascular responses to postural change from sitting to standing involve complex interactions between the autonomic nervous system, which regulates blood pressure, and cerebral autoregulation, which maintains cerebral perfusion. We present a mathematical model that can predict dynamic changes in beat-to-beat arterial blood pressure and middle cerebral artery blood flow velocity during postural change from sitting to standing. Our cardiovascular model utilizes 11 compartments to describe blood pressure, blood flow, compliance, and resistance in the heart and systemic circulation. To include dynamics due to the pulsatile nature of blood pressure and blood flow, resistances in the large systemic arteries are modeled using nonlinear functions of pressure. A physiologically based submodel is used to describe effects of gravity on venous blood pooling during postural change. Two types of control mechanisms are included: 1) autonomic regulation mediated by sympathetic and parasympathetic responses, which affect heart rate, cardiac contractility, resistance, and compliance, and 2) autoregulation mediated by responses to local changes in myogenic tone, metabolic demand, and CO(2) concentration, which affect cerebrovascular resistance. Finally, we formulate an inverse least-squares problem to estimate parameters and demonstrate that our mathematical model is in agreement with physiological data from a young subject during postural change from sitting to standing.     

Population HIV-1 dynamics in vivo: applicable models and inferential tools for virological data from AIDS clinical trials

In this paper, we introduce a novel application of hierarchical nonlinear mixed-effect models to HIV dynamics. We show that a simple model with a sum of exponentials can give a good fit to the observed clinical data of HIV-1 dynamics (HIV-1 RNA copies) after initiation of potent antiviral treatments and can also be justified by a biological compartment model for the interaction between HIV and its host cells. This kind of model enjoys both biological interpretability and mathematical simplicity after reparameterization and simplification. A model simplification procedure is proposed and illustrated through examples. We interpret and justify various simplified models based on clinical data taken during different phases of viral dynamics during antiviral treatments. We suggest the hierarchical nonlinear mixed-effect model approach for parameter estimation and other statistical inferences. In the context of an AIDS clinical trial involving patients treated with a combination of potent antiviral agents, we show how the models may be used to draw biologically relevant interpretations from repeated HIV-1 RNA measurements and demonstrate the potential use of the models in clinical decision-making.     

Estimating the distribution of selection coefficients from phylogenetic data using sitewise mutation-selection models

Estimation of the distribution of selection coefficients of mutations is a long-standing issue in molecular evolution. In addition to population-based methods, the distribution can be estimated from DNA sequence data by phylogenetic-based models. Previous models have generally found unimodal distributions where the probability mass is concentrated between mildly deleterious and nearly neutral mutations. Here we use a sitewise mutation-selection phylogenetic model to estimate the distribution of selection coefficients among novel and fixed mutations (substitutions) in a data set of 244 mammalian mitochondrial genomes and a set of 401 PB2 proteins from influenza. We find a bimodal distribution of selection coefficients for novel mutations in both the mitochondrial data set and for the influenza protein evolving in its natural reservoir, birds. Most of the mutations are strongly deleterious with the rest of the probability mass concentrated around mildly deleterious to neutral mutations. The distribution of the coefficients among substitutions is unimodal and symmetrical around nearly neutral substitutions for both data sets at adaptive equilibrium. About 0.5% of the nonsynonymous mutations and 14% of the nonsynonymous substitutions in the mitochondrial proteins are advantageous, with 0.5% and 24% observed for the influenza protein. Following a host shift of influenza from birds to humans, however, we find among novel mutations in PB2 a trimodal distribution with a small mode of advantageous mutations.     

Pressor reactions to psychological stress and prediction of future blood pressure: data from the Whitehall II Study.

OBJECTIVE--To examine whether reactions of blood pressure to psychological stress predict future blood pressure. DESIGN--Blood pressure was recorded at a medical screening examination after which pressor reactions to a psychological stress task were determined. Follow up measurement of blood pressure was undertaken, on average, 4.9 years later. SETTING--20 civil service departments in London. SUBJECTS--1003 male civil servants aged between 35 and 55 years at entry to the study. MAIN OUTCOME MEASURE--Blood pressure at follow up screening. RESULTS--Reactions of systolic blood pressure to stress correlated positively with systolic blood pressure at follow up screening (r = 0.22, P < 0.01). The dominant correlate of follow up blood pressure was blood pressure at initial screening (r = 0.60; P < 0.01 between initial and follow up systolic blood pressure; r = 0.59, P < 0.01 between initial and follow up diastolic blood pressure). Stepwise multiple regression analysis indicated that reactions to the stressor provided minimal prediction of follow up blood pressure over and above that afforded by blood pressure at initial screening. In the case of follow up systolic blood pressure, systolic reactions to stress accounted for only 1% of follow up variance; systolic blood pressure at initial screening accounted for 34%. With regard to diastolic blood pressure at follow up, the independent contribution from diastolic reactions to stress was less than 1%. CONCLUSION--Pressor reactions to psychological stress provide minimal independent prediction of blood pressure at follow up. Measurement of reactivity is not a useful clinical index of the course of future blood pressure.     

Genome-wide linkage analysis of systolic blood pressure slope using the Genetic Analysis Workshop 13 data sets

Systolic blood pressure (SBP) is an age-dependent complex trait for which both environmental and genetic factors may play a role in explaining variability among individuals. We performed a genome-wide scan of the rate of change in SBP over time on the Framingham Heart Study data and one randomly selected replicate of the simulated data from the Genetic Analysis Workshop 13. We used a variance-component model to carry out linkage analysis and a Markov chain Monte Carlo-based multiple imputation approach to recover missing information. Furthermore, we adopted two selection strategies along with the multiple imputation to deal with subjects taking antihypertensive treatment. The simulated data were used to compare these two strategies, to explore the effectiveness of the multiple imputation in recovering varying degrees of missing information, and its impact on linkage analysis results. For the Framingham data, the marker with the highest LOD score for SBP slope was found on chromosome 7. Interestingly, we found that SBP slopes were not heritable in males but were for females; the marker with the highest LOD score was found on chromosome 18. Using the simulated data, we found that handling treated subjects using the multiple imputation improved the linkage results. We conclude that multiple imputation is a promising approach in recovering missing information in longitudinal genetic studies and hence in improving subsequent linkage analyses.