MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

Causal Inference in Observational Studies with Outcome-Dependent Sampling

In this paper, we consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals are drawn from a population. On these individuals, information is obtained on treatment, outcome, and a few low-dimensional confounders. These individuals are then stratified according to these factors. In the second phase, a random sub-sample of individuals are drawn from each stratum, with known, stratum-specific selection probabilities. On these individuals, a rich set of confounding factors are collected. In this setting, we introduce four estimators: (1) simple inverse weighted, (2) locally efficient, (3) doubly robust and (4)enriched inverse weighted. We evaluate the finite-sample performance of these estimators in a simulation study. We also use our methodology to estimate the causal effect of trauma care on in-hospital mortality using data from the National Study of Cost and Outcomes of Trauma.

Peroxide bond-dependent antiplasmodial specificity of artemisinin and OZ277 (RBx11160)

Using nonperoxidic analogs of artemisinin and OZ277 (RBx11160), the strong in vitro antiplasmodial activities of the latter two compounds were shown to be peroxide bond dependent. In contrast, the weak activities of artemisinin and OZ277 against six other protozoan parasites were peroxide bond independent. These data support the iron-dependent artemisinin alkylation hypothesis.

Direct adipotropic actions of atorvastatin: differentiation state-dependent induction of apoptosis, modulation of endocrine function, and inhibition of glucose uptake

Statins exert anti-inflammatory, anti-atherogenic actions. The mechanisms responsible for these effects remain only partially elucidated. Diabetes and obesity are characterized by low-grade inflammation. Metabolic and endocrine adipocyte dysfunction is known to play a crucial role in the development of these disorders and the related cardiovascular complications. Thus, direct modulation of adipocyte function may represent a mechanism of pleiotropic statin actions. We investigated effects of atorvastatin on apoptosis, differentiation, endocrine, and metabolic functions in murine white and brown adipocyte lines. Direct exposure of differentiating preadipocytes to atorvastatin strongly reduced lipid accumulation and diminished protein expression of the differentiation marker CCAAT/enhancer binding protein-beta (CEBP-beta). In fully differentiated adipocytes, however, lipid accumulation remained unchanged after chronic atorvastatin treatment. Furthermore, cell viability was reduced in response to atorvastatin treatment in proliferating and differentiating preadipocytes, but not in differentiated cells. Moreover, atorvastatin induced apoptosis and inhibited protein kinase B (AKT) phosphorylation in proliferating and differentiating preadipocytes, but not in differentiated adipocytes. On the endocrine level, direct atorvastatin treatment of differentiated white adipocytes enhanced expression of the pro-inflammatory adipokine interleukin-6 (IL-6), and downregulated expression of the insulin-mimetic and anti-inflammatory adipokines visfatin and adiponectin. Finally, these direct adipotropic endocrine effects of atorvastatin were paralleled by the acute inhibition of insulin-induced glucose uptake in differentiated white adipocytes, while protein expression of the thermogenic uncoupling protein-1 (UCP-1) in brown adipocytes remained unchanged. Taken together, our data for the first time demonstrate direct differentiation state-dependent effects of atorvastatin including apoptosis, modulation of pro-inflammatory and glucostatic adipokine expression, and insulin resistance in adipose cells. These differential interactions may explain variable clinical observations.

Age and gender-dependent alternative splicing of P/Q-type calcium channel EF-hand

Ca(v)2.1 Ca(2+) channels (P/Q-type), which participate in various key roles in the CNS by mediating calcium influx, are extensively spliced. One of its alternatively-spliced exons is 37, which forms part of the EF hand. The expression of exon 37a (EFa form), but not exon 37b (EFb form), confers the channel an activity-dependent enhancement of channel opening known as Ca(2+)-dependent facilitation (CDF). In this study, we analyzed the trend of EF hand splice variant distributions in mouse, rat and human brain tissues. We observed a developmental switch in rodents, as well as an age and gender bias in human brain tissues, suggestive of a possible role of these EF hand splice variants in neurophysiological specialization. A parallel study performed on rodent brains showed that the data drawn from human and rodent tissues may not necessarily correlate in the process of aging.

Modeling of electroosmotic and electrophoretic mobilization in capillary and microchip isoelectric focusing

Our dynamic capillary electrophoresis model which uses material specific input data for estimation of electroosmosis was applied to investigate fundamental aspects of isoelectric focusing (IEF) in capillaries or microchannels made from bare fused-silica (FS), FS coated with a sulfonated polymer, polymethylmethacrylate (PMMA) and poly(dimethylsiloxane) (PDMS). Input data were generated via determination of the electroosmotic flow (EOF) using buffers with varying pH and ionic strength. Two models are distinguished, one that neglects changes of ionic strength and one that includes the dependence between electroosmotic mobility and ionic strength. For each configuration, the models provide insight into the magnitude and dynamics of electroosmosis. The contribution of each electrophoretic zone to the net EOF is thereby visualized and the amount of EOF required for the detection of the zone structures at a particular location along the capillary, including at its end for MS detection, is predicted. For bare FS, PDMS and PMMA, simulations reveal that EOF is decreasing with time and that the entire IEF process is characterized by the asymptotic formation of a stationary steady-state zone configuration in which electrophoretic transport and electroosmotic zone displacement are opposite and of equal magnitude. The location of immobilization of the boundary between anolyte and most acidic carrier ampholyte is dependent on EOF, i.e. capillary material and anolyte. Overall time intervals for reaching this state in microchannels produced by PDMS and PMMA are predicted to be similar and about twice as long compared to uncoated FS. Additional mobilization for the detection of the entire pH gradient at the capillary end is required. Using concomitant electrophoretic mobilization with an acid as coanion in the catholyte is shown to provide sufficient additional cathodic transport for that purpose. FS capillaries dynamically double coated with polybrene and poly(vinylsulfonate) are predicted to provide sufficient electroosmotic pumping for detection of the entire IEF gradient at the cathodic column end.

Angiopoietin-2 deficiency decelerates age-dependent vascular changes in the mouse retina

Retinae of aged humans show signs of vascular regression. Vascular regression involves a mismatch between Angiopoietin-2 (Ang-2) and vascular endothelial growth factor (VEGF) expression. We used heterozygous Ang-2 deficient (Ang2LacZ) mice to evaluate murine retinal vascular changes and gene expression of growth factors. Vascular changes were assessed by quantitative retinal morphometry and gene expression levels of growth factors were measured by quantitative PCR. The numbers of endothelial cells and pericytes did not change in the Ang2LacZ retinae with age, whereas they decreased throughout the age spectrum studied in the wild type retinae. Moreover, vascular regression significantly decelerated in the heterozygous Ang2LacZ retinae (200% to 1 month), while the formation of acellular capillaries was significantly increased at 13 months in the wild type retinae (340% to 1 month). Gene expression analysis revealed that VEGF, Ang-1, PDGF-B and Ang2 mRNA levels were decreased in the wild type retinae at 9 month of age. However, the decrease of Ang-2 was smaller compared with other genes. While VEGF levels dropped in wild type mice up to 60% compared to 1 month, VEGF increased in heterozygous Ang-2 deficient retinae at an age of 9 months (141% to 1 month). Similarly, Ang-1 levels decreased in wild type mice (45% to 1 month), but remained stable in Ang2LacZ mice. These data suggest that Ang-2 gene dose reduction decelerates vasoregression in the retina with age. This effect links to higher levels of survival factors such as VEGF and Ang-1, suggesting that the ratio of these factors is critical for capillary cell survival.

Time-related, cross-sectional and prospective follow-up of pancreatic endocrine function after pancreas allograft transplantation in type 1 (insulin-dependent) diabetic patients

It has been established that successful pancreas transplantation in Type 1 (insulin-dependent) diabetic patients results in normal but exaggerated phasic glucose-induced insulin secretion, normal intravenous glucose disappearance rates, improved glucose recovery from insulin-induced hypoglycaemia, improved glucagon secretion during insulin-induced hypoglycaemia, but no alterations in pancreatic polypeptide responses to hypoglycaemia. However, previous reports have not segregated the data in terms of the length of time following successful transplantation and very little prospective data collected over time in individual patients has been published. This article reports that in general there are no significant differences in the level of improvement when comparing responses as early as three months post-operatively up to as long as two years post-operatively when examining the data cross-sectionally in patients who have successfully maintained their allografts. Moreover, this remarkable constancy in pancreatic islet function is also seen in a smaller group of patients who have been examined prospectively at various intervals post-operatively. It is concluded that successful pancreas transplantation results in remarkable improvements in Alpha and Beta cell but not PP cell function that are maintained for at least one to two years.

Simple beam models for Monte Carlo photon beam dose calculations in radiotherapy

Monte Carlo (code GEANT) produced 6 and 15 MV phase space (PS) data were used to define several simple photon beam models. For creating the PS data the energy of starting electrons hitting the target was tuned to get correct depth dose data compared to measurements. The modeling process used the full PS information within the geometrical boundaries of the beam including all scattered radiation of the accelerator head. Scattered radiation outside the boundaries was neglected. Photons and electrons were assumed to be radiated from point sources. Four different models were investigated which involved different ways to determine the energies and locations of beam particles in the output plane. Depth dose curves, profiles, and relative output factors were calculated with these models for six field sizes from 5x5 to 40x40cm2 and compared to measurements. Model 1 uses a photon energy spectrum independent of location in the PS plane and a constant photon fluence in this plane. Model 2 takes into account the spatial particle fluence distribution in the PS plane. A constant fluence is used again in model 3, but the photon energy spectrum depends upon the off axis position. Model 4, finally uses the spatial particle fluence distribution and off axis dependent photon energy spectra in the PS plane. Depth dose curves and profiles for field sizes up to 10x10cm2 were not model sensitive. Good agreement between measured and calculated depth dose curves and profiles for all field sizes was reached for model 4. However, increasing deviations were found for increasing field sizes for models 1-3. Large deviations resulted for the profiles of models 2 and 3. This is due to the fact that these models overestimate and underestimate the energy fluence at large off axis distances. Relative output factors consistent with measurements resulted only for model 4.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Age-dependent differences in demographics, risk factors, co-morbidity, etiology, management, and clinical outcome of acute ischemic stroke

BACKGROUND : Comparisons between younger and older stroke patients including comorbidities are limited. METHODS : Prospective data of consecutive patients with first ever acute ischemic stroke were compared between younger ( 45 years). RESULTS : Among 1004 patients, 137 (14 %) were

TRAIL-induced survival and proliferation of SCLC cells is mediated by ERK and dependent on TRAIL-R2/DR5 expression in the absence of caspase-8

Small cell lung cancer (SCLC) is characterized by an aggressive phenotype and acquired resistance to a broad spectrum of anticancer agents. TNF-related apoptosis-inducing ligand (TRAIL) has been considered as a promising candidate for safe and selective induction of tumor cell apoptosis without toxicity to normal tissues. Here we report that TRAIL failed to induce apoptosis in SCLC cells and instead resulted in an up to 40% increase in proliferation. TRAIL-induced SCLC cell proliferation was mediated by extracellular signal-regulated kinase 1 and 2, and dependent on the expression of surface TRAIL-receptor 2 (TRAIL-R2) and lack of caspase-8, which is frequent in SCLC. Treatment of SCLC cells with interferon-gamma (IFN-gamma) restored caspase-8 expression and facilitated TRAIL-induced apoptosis. The overall loss of cell proliferation/viability upon treatment with the IFN-gamma-TRAIL combination was 70% compared to TRAIL-only treated cells and more than 30% compared to untreated cells. Similar results were obtained by transfection of cells with a caspase-8 gene construct. Altogether, our data suggest that TRAIL-R2 expression in the absence of caspase-8 is a negative determinant for the outcome of TRAIL-based cancer therapy, and provides the rationale for using IFN-gamma or other strategies able to restore caspase-8 expression to convert TRAIL from a pro-survival into a death ligand.

IL-3 induces a Pim1-dependent antiapoptotic pathway in primary human basophils

The contribution of basophils in allergic disease and other Th2-type immune responses depends on their persistence at sites of inflammation, but the ligands and molecular pathways supporting basophil survival are largely unknown. The comparison of rates of apoptosis and of the expression of antiapoptotic proteins in different human granulocyte types revealed that basophils have a considerably longer spontaneous life span than neutrophils and eosinophils consistent with high levels of constitutive Bcl-2 expression. Interleukin-3 (IL-3) is the only ligand that efficiently protects basophils from apoptosis as evidenced by screening a large number of stimuli. IL-3 up-regulates the expression of the antiapoptotic proteins cIAP2, Mcl-1, and Bcl-X(L) and induces a rapid and sustained de novo expression of the serine/threonine kinase Pim1 that closely correlates with cytokine-enhanced survival. Inhibitor studies and protein transduction of primary basophils using wild-type and kinase-dead Pim1-Tat fusion-proteins demonstrate the functional importance of Pim1 induction in the IL-3-enhanced survival. Our data further indicate that the antiapoptotic Pim1-mediated pathway operates independently of PI3-kinase but involves the activation of p38 MAPK. The induction of Pim1 leading to PI3-kinase-independent survival as described here for basophils may also be a relevant antiapoptotic mechanism in other terminally differentiated leukocyte types.

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.