An empirical comparison of methods for meta-analysis of diagnostic accuracy showed hierarchical models are necessary

OBJECTIVE: Meta-analysis of studies of the accuracy of diagnostic tests currently uses a variety of methods. Statistically rigorous hierarchical models require expertise and sophisticated software. We assessed whether any of the simpler methods can in practice give adequately accurate and reliable results. STUDY DESIGN AND SETTING: We reviewed six methods for meta-analysis of diagnostic accuracy: four simple commonly used methods (simple pooling, separate random-effects meta-analyses of sensitivity and specificity, separate meta-analyses of positive and negative likelihood ratios, and the Littenberg-Moses summary receiver operating characteristic [ROC] curve) and two more statistically rigorous approaches using hierarchical models (bivariate random-effects meta-analysis and hierarchical summary ROC curve analysis). We applied the methods to data from a sample of eight systematic reviews chosen to illustrate a variety of patterns of results. RESULTS: In each meta-analysis, there was substantial heterogeneity between the results of different studies. Simple pooling of results gave misleading summary estimates of sensitivity and specificity in some meta-analyses, and the Littenberg-Moses method produced summary ROC curves that diverged from those produced by more rigorous methods in some situations. CONCLUSION: The closely related hierarchical summary ROC curve or bivariate models should be used as the standard method for meta-analysis of diagnostic accuracy.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Time-dependent hierarchical organization of spatial working memory: a transcranial magnetic stimulation study

The performance of memory-guided saccades with two different delays (3 and 30 s of memorization) was studied in seven healthy subjects. Double-pulse transcranial magnetic stimulation (dTMS) with an interstimulus interval of 100 ms was applied over the right dorsolateral prefrontal cortex (DLPFC) early (1 s after target presentation) and late (28 s after target presentation). Early stimulation significantly increased in both delays the percentage of error in amplitude (PEA) of contralateral memory-guided saccades compared to the control experiment without stimulation. dTMS applied late in the delay had no significant effect on PEA. Furthermore, we found a significantly smaller effect of early stimulation in the long-delay paradigm. These results suggest a time-dependent hierarchical organization of the spatial working memory with a functional dominance of DLPFC during the early memorization, independent from the memorization delay. For a long memorization delay, however, working memory seems to have an additional, DLPFC-independent component.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

The content and composition of lipids in the digital cushion of the bovine claw with respect to age and location--a preliminary report

The pads of the bovine digital cushion, which serves as a shock absorber, have specific anatomical structures to cope with the substantial forces acting within the claw. To gain more information on the lipid composition and content of the pads, horn shoes from 12 slaughtered heifers and cows were removed and different samples of the pads excised with a scalpel. Pad lipids were extracted and the fatty acid composition determined by gas chromatography. Fat from perirenal and subcutaneous adipose tissues served as a comparison. Overall, this fat contained a higher quantity of extracted lipids than that of the claw pads and did not differ between heifers and cows. In contrast, lipid content in the pads was significantly higher in the cows than in the heifers. In both groups, the lipid content of the middle and abaxial pads, which are situated directly under the distal phalanx, was lower than in the pads of the other locations. The lipids in all pads contained >77% monounsaturated fatty acids (MUFA), differing sharply from the adipose tissue with values <51%. Among the polyunsaturated fatty acids (PUFA) a significantly higher proportion of arachidonic acid (AA) was found in the heifer pads than in those of the cows, whereas the proportion of AA was similar in the adipose tissue of all animals. The proportion of AA in the pad lipids also varied between the defined locations with the highest proportion found in locations that showed the lowest lipid content and was related to the age of the animal.

PTH-related protein is released into the mother's bloodstream during location: evidence for beneficial effects on maternal calcium-phosphate metabolism

Recent studies have indicated that parathyroid hormone-related protein (PTHrP) may have important actions in lactation, affecting the mammary gland, and also calcium metabolism in the newborn and the mother. However, there are as yet no longitudinal studies to support the notion of an endocrine role of this peptide during nursing. We studied a group of 12 nursing mothers, mean age 32 years, after they had been nursing for an average of 7 weeks (B) and also 4 months after stopping nursing (A). It was assumed that changes occurring between A and B correspond to the effect of lactation. Blood was assayed for prolactin (PRL), PTHrP (two-site immunoradiometric assay with sheep antibody against PTHrP(1-40), and goat antibody against PTHrP(60-72), detection limit 0.3 pmol/l), intact PTH (iPTH), ionized calcium (Ca2+), 25-hydroxyvitamin D3 (25(OH)D3) and 1,25-dihydroxyvitamin D3 (1,25(OH)2D3), alkaline phosphatase (alkP), as well as for creatinine (Cr), protein, phosphorus (P), and total calcium (Ca). Fasting 2-h urine samples were analyzed for Ca excretion (CaE) and renal phosphate threshold (TmP/GFR). PRL was significantly higher during lactation than after weaning (39 +/- 10 vs. 13 +/- 9 micrograms/l; p = 0.018) and so was PTHrP (2.8 +/- 0.35 vs. 0.52 +/- 0.04 pmol/l; p = 0.002), values during lactation being above the normal limit (1.3 pmol/l) in all 12 mothers. There was a significant correlation between PRL and PTHrP during lactation (r = 0.8, p = 0.002). Whole blood Ca2+ did not significantly change from A (1.20 +/- 0.02 mmol/l) to B (1.22 +/- 0.02, mmol/l), whereas total Ca corrected for protein (2.18 +/- 0.02 mmol/l) or uncorrected (2.18 +/- 0.02 mmol/l) significantly rose during lactation (2.31 +/- 0.02 mmol/l, p = 0.003 and 2.37 +/- 0.03 mmol/l, p = 0.002, respectively). Conversely, iPTH decreased during lactation (3.47 +/- 0.38 vs. 2.11 +/- 0.35 pmol/l, A vs. B, p = 0.02). Serum-levels of 25(OH)D3 and 1,25(OH)2D3 did not significantly change from A to B (23 +/- 2.3 vs. 24 +/- 1.9 ng/ml and 29.5 +/- 6.0 vs. 21.9 +/- 1.8 pg/ml, respectively). Both TmP/GFR and P were higher during lactation than after weaning (1.15 +/- 0.03 vs. 0.86 +/- 0.05 mmol/l GF, p = 0.003 and 1.25 +/- 0.03 vs. 0.96 +/- 0.05 mmol/l, p = 0.002, respectively) as was alkP (74.0 +/- 7.1 vs. 52.6 +/- 6.9 U/l, p = 0.003). CaE did not differ between A and B (0.015 +/- 0.003 vs. 0.017 +/- 0.003 mmol/l GF, A vs. B, NS). We conclude that lactation is accompanied by an increase in serum PRL. This is associated with a release of PTHrP into the maternal blood circulation. A rise in total plasma Ca ensues, probably in part by increased bone turnover as suggested by the elevation of alkP. PTH secretion falls, with a subsequent rise of TmP/GFR and plasma P despite high plasma levels of PTHrP.