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关键词： system dynamics   body weight regulation   glycogen levels   dietary fat   exercise  

摘要： Objective: A systems dynamics computer model was developed to examine how the interactions between carbohydrate and fat metabolism influence body weight regulation. It reflects the operation of a two reservoir-system: one representing the body's limited glycogen, and the other, its large fat reserves. The outflows from the reservoirs correspond to the oxidation of glucose and fat, whose relative contributions are affected by the size of the prevailing glycogen and fat reserves. Together, they meet the body's energy expenditure. Replenishments occur three times per day, in portions restoring total glycogen content to specific levels. A parameter mimicking the action of insulin is necessary to create realistic responses. Research Methods and Procedures: The model was run for 125-day periods to establish the degree of adiposity for which rates of fat oxidation become commensurate with fat intake and the influence thereon of various dietary, environmental, lifestyle, and inherited variables. Results: Equivalent degrees of adiposity can be sustained under a variety of conditions. For instance, the impact on steady-state body fat contents of a 10% increase or decrease in. the energy provided by dietary fat is offset by a 26-gram decrease or increase in mean glycogen levels. Discussion: Environmental factors such as food diversity, palatability, and availability can be expected to raise the range within which glycogen levels are habitually maintained. This restrains fat oxidation, until expansion of the fat mass is sufficient to promote fat oxidation to a rate commensurate with dietary fat intake. This metabolic leverage can explain why increased food offerings tend to raise the prevalence of obesity.

关键词： bioinformatics   chance correlation   class prediction   classification   decision forest   prediction confidence   prostate cancer   proteomics   SELDI-TOF  

摘要： Class prediction using "omics" data is playing an increasing role in toxicogenomics, diagnosis/prognosis, and risk assessment. These data are usually noisy and represented by relatively few samples and a very large number of predictor variables (e.g., genes of DNA microarray data or m/z peaks of mass spectrometry data). These characteristics manifest the importance of assessing potential random correlation and overfitting of noise for a classification model based on omics data. We present a novel classification method, decision forest (DF), for class prediction using omics data. DF combines the results of multiple heterogeneous but comparable decision tree (DT) models to produce a consensus prediction. The method is less prone to overfitting of noise and chance correlation. A DF model was developed to predict presence of prostate cancer using a proteomic data set generated from surface-enhanced laser deposition/ ionization time-of-flight mass spectrometry (SELDI-TOF MS). The degree of chance correlation and prediction confidence of the model was rigorously assessed by extensive cross-validation and randomization testing. Comparison of model prediction with imposed random correlation demonstrated biologic relevance of the model and the reduction of overfitting in DF. Furthermore, two confidence levels (high and low confidences) were assigned to each prediction, where most misclassifications were associated with the low-confidence region. For the high-confidence prediction, the model achieved 99.2% sensitivity and 98.2% specificity. The model also identified a list of significant peaks that could be useful for biomarker identification. DF should be equally applicable to other omics data such as gene expression data or metabolomic data. The DF algorithm is available upon request.

摘要： Southeastern Alaska, encompassing the glaciated Chugach-St. Elias range (Figure 1), is one of the premier locations where tectonics, orogenesis, glacial erosion, landscape modification, and continental margin sedimentation can be studied in unison, allowing for quantitative models to be developed linking this suite of processes [e.g., Jaeger et al, 2001 ]. This area is an exceptional natural laboratory for studying a range of geologic problems (Figures 2 and 3), including the links between orogenic processes and continental accretion, glacial landscape modification, and sedimentation. Geologic processes operate at rapid rates along the margin, which allows concurrent data collection on tectonic deformation, uplift, erosion, and sedimentation and development of comprehensive geodynamic models connecting these diverse *** active processes in southeastern Alaska are comparable or significantly greater than those studied in the Himalayan orogeny, and include extremely high sediment yields, active faults associated with mountains and valley glaciers, and orogeny coinciding with extensive glacial cover.

关键词： 临床护士   医学检验   采集标本   医学模式   改变   作用   原因  

摘要： 随着科学技术的发展,医学模式的改变,手工操作的医学检验逐步变为机械化的操作.这样,医学检验的大部分标本的采集都由临床护士来完成.所以,临床护士在医学检验中有着不可低估的重要作用.现归纳我科近年来临床护士采集标本不正确导致结果误差的原因,报告如下.

关键词： 电信公司   上市公司   劳动合同用工   用工转化形式   劳务派遣公司  

摘要： 上市公司的用工问题是影响公司、股东、员工、社会多方利益的大问题。如何采取措施减员或不增员而增效,又不影响公司的实际用工需求,是值得探讨的问题。

关键词： 重数   强相互作用   夸克   非奇异   粒子产率   同位旋   QCD   抑制因子   比值   味道  

摘要： 通过比较不同味道初始夸克碎裂的带电粒子多重数可以对强相互作用味道无关性进行检验 .计算了e+e- 湮没成轻味夸克u ,d ,s碎裂的粒子多重数 ,发现不同味道夸克事例中 ,平均粒子产率 ,同位旋对称性 ,由奇异与非奇异粒子多重数比值确定的奇异抑制因子等都与初始夸克味道有关 ,而且这种依赖性在低能时更加明显 .但 3种轻味夸克事例的平均带电粒子多重数近似相等 ,这与QCD强相互作用与味道无关的预言一致 .

摘要： Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based oil these differences, a classification procedure (SIMCA) showed a very,cry accurate classification of the validation set samples: all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content or these samples was considered in two ways: building up a global model for all the growth stages, and building tip local models for each stage, separately. The best prediction results for Crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local Model for the harvest stage samples.

关键词： Oligonucleotide Array Sequence Analysis   Selection (Genetics)   Colonic Neoplasms   Gene Expression Profiling   Humans   Predictive Value of Tests   Skin  

摘要： DNA microarray technology provides useful tools for profiling global gene expression patterns in different cell/tissue samples. One major challenge is the large number of genes relative to the number of samples. The use of all genes can suppress or reduce the performance of a classification rule due to the noise of nondiscriminatory genes. Selection of an optimal subset from the original gene set becomes an important prestep in sample classification. In this study, we propose a family-wise error (FWE) rate approach to selection of discriminatory genes for two-sample or multiple-sample classification. The FWE approach controls the probability of the number of one or more false positives at a prespecified level. A public colon cancer data set is used to evaluate the performance of the proposed approach for the two classification methods: k nearest neighbors (k-NN) and support vector machine (SVM). The selected gene sets from the proposed procedure appears to perform better than or comparable to several results reported in the literature using the univariate analysis without performing multivariate search. In addition, we apply the FWE approach to a toxicogenomic data set with nine treatments (a control and eight metals, As, Cd, Ni, Cr, Sb, Pb, Cu, and AsV) for a total of 55 samples for a multisample classification. Two gene sets are considered: the gene set Omega(F) formed by the ANOVA F-test, and a gene set Omega(T) formed by the union of one-versus-all t-tests. The predicted accuracies are evaluated using the internal and external crossvalidation. Using the SVM classification, the overall accuracies to predict 55 samples into one of the nine treatments are above 80% for internal crossvalidation. Omega(F) has slightly higher accuracy rates than Omega(T). The overall predicted accuracies are above 70% for the external crossvalidation;the two gene sets Omega(T) and delta(F) performed equally well.

关键词： exposure misclassification   drug exposure   claims databases   selective COX-2 inhibitors   bias   epidemiologic methods  

摘要： Purpose Free drug samples are widely used in clinical practice. We were concerned about free sample drug utilization as a source of misclassification in pharmacoepidemiology research using claims data that may result in biased effect estimates. Methods We investigated the magnitude of potential bias with sensitivity analyses based on a published study that examined cardiovascular risk associated with selective cyclooxygenase 2 (COX-2) inhibitors. We derived an estimate of free sample drug utilization with market data for rofexcoxib and calculated sensitivity of the exposure ascertainment method using claims data. We corrected the incidence rate ratio assuming the observed unexposed incidence rate was actually a weighted average rate of the truly unexposed and free sample drug users. The impact of exposure misclassification measured as the percentage change from a corrected to the reported crude incidence rate ratio was examined under a range of free sample drug utilization proportions and unexposed cohort sizes. Results The proportion of free sample drug utilization of all rofecoxib use in our base case scenario was 15.48%, resulting in sensitivity of 84.52% for exposure ascertainment. The magnitude of bias was an underestimation of the unadjusted incidence rate ratio by 0.03%. With a free sample drug utilization proportion of 1.48% and the same unexposed cohort size of 237 975 person-years, the underestimation was 0.003%. If the unexposed cohort were 975 person-years given a 15.48% proportion, the underestimation was 8.82%. Conclusions In the pharmacoepiderniology study, we examined that uses claims data to ascertain drug exposure, our results suggest that adjustment for free sample drug utilization is probably not warranted. Copyright (C) 2004 John Wiley Sons, Ltd.