Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

Inflammasome-dependent IFN-γ drives pathogenesis in Streptococcus pneumoniae meningitis

The pathology associated with Streptococcus pneumoniae meningitis results largely from activation of immune-associated pathways. We systematically investigated the production of IFN subtypes, as well as their influence on pathology, in a mouse model of S. pneumoniae meningitis. Despite the occurrence of a mixed IFN type I/II gene signature, no evidence for production or involvement of type I IFNs in disease progression was found. In contrast, type II IFN (IFN-γ) was strongly induced, and IFN-γ(-/-) mice were significantly protected from severe disease. Using intracellular cytokine staining and targeted cell-depletion approaches, NK cells were found to be the dominant source of IFN-γ. Furthermore, production of IFN-γ was found to be dependent upon ASC and IL-18, indicating that an ASC-dependent inflammasome pathway was responsible for mediating IFN-γ induction. The influence of IFN-γ gene deletion on a range of processes known to be involved in bacterial meningitis pathogenesis was examined. Although neutrophil numbers in the brain were similar in infected wild-type and IFN-γ(-/-) mice, both monocyte recruitment and CCL2 production were less in infected IFN-γ(-/-) mice compared with infected wild-type controls. Additionally, gene expression of NO synthase was strongly diminished in infected IFN-γ(-/-) mice compared with infected controls. Finally, bacterial clearance was enhanced in IFN-γ(-/-) mice, although the underlying mechanism remains unclear. Together, these data suggest that inflammasome-dependent IFN-γ contributes via multiple pathways to pathology during S. pneumoniae meningitis.

Using Micro-Gravity Techniques to Map Alluvium Thickness and Pleistocene Location of the West Branch of the Susquehanna River Near Muncy, Pennsylvania

Laurentide glaciation during the early Pleistocene (~970 ka) dammed the southeast-flowing West Branch of the Susquehanna River (WBSR), scouring bedrock and creating 100-km-long glacial Lake Lesley near the Great Bend at Muncy, Pennsylvania (Ramage et al., 1998). Local drill logs and well data indicate that subsequent paleo-outwash floods and modern fluvial processes have deposited as much as 30 meters of alluvium in this area, but little is known about the valley fill architecture and the bedrock-alluvium interface. By gaining a greater understanding of the bedrock-alluvium interface the project will not only supplement existing depth to bedrock information, but also provide information pertinent to the evolution of the Muncy Valley landscape. This project determined if variations in the thickness of the valley fill were detectable using micro-gravity techniques to map the bedrock-alluvium interface. The gravity method was deemed appropriate due to scale of the study area (~30 km2), ease of operation by a single person, and the available geophysical equipment. A LaCoste and Romberg Gravitron unit was used to collect gravitational field readings at 49 locations over 5 transects across the Muncy Creek and Susquehanna River valleys (approximately 30 km2), with at least two gravity base stations per transect. Precise latitude, longitude and ground surface elevation at each location were measured using an OPUS corrected Trimble RTK-GPS unit. Base stations were chosen based on ease of access due to the necessity of repeat measurements. Gravity measurement locations were selected and marked to provide easy access and repeat measurements. The gravimeter was returned to a base station within every two hours and a looping procedure was used to determine drift and maximize confidence in the gravity measurements. A two-minute calibration reading at each station was used to minimize any tares in the data. The Gravitron digitally recorded finite impulse response filtered gravity measurements every 20 seconds at each station. A measurement period of 15 minutes was used for each base station occupation and a minimum of 5 minutes at all other locations. Longer or multiple measurements were utilized at some sites if drift or other externalities (i.e. train or truck traffic) were effecting readings. Average, median, standard deviation and 95% confidence interval were calculated for each station. Tidal, drift, latitude, free-air, Bouguer and terrain corrections were then applied. The results show that the gravitational field decreases as alluvium thickness increases across the axes of the Susquehanna River and Muncy Creek valleys. However, the location of the gravity low does not correspond with the present-day location of the West Branch of the Susquehanna River (WBSR), suggesting that the WBSR may have been constrained along Bald Eagle Mountain by a glacial lobe originating from the Muncy Creek Valley to the northeast. Using a 3-D inversion model, the topography of the bedrock-alluvium interface was determined over the extent of the study area using a density contrast of -0.8 g/cm3. Our results are consistent with the bedrock geometry of the area, and provide a low-cost, non-invasive and efficient method for exploring the subsurface and for supplementing existing well data.

“All Data is Credit Data,” or, On Close Reading as a Reciprocal Process in Digital Knowledge Environments

The new knowledge environments of the digital age are oen described as places where we are all closely read, with our buying habits, location, and identities available to advertisers, online merchants, the government, and others through our use of the Internet. This is represented as a loss of privacy in which these entities learn about our activities and desires, using means that were unavailable in the pre-digital era. This article argues that the reciprocal nature of digital networks means 1) that the privacy issues that we face online are not radically different from those of the pre-Internet era, and 2) that we need to reconceive of close reading as an activity of which both humans and computer algorithms are capable.

A physics-based correction model for homogenizing sub-daily temperature series

A new physics-based technique for correcting inhomogeneities present in sub-daily temperature records is proposed. The approach accounts for changes in the sensor-shield characteristics that affect the energy balance dependent on ambient weather conditions (radiation, wind). An empirical model is formulated that reflects the main atmospheric processes and can be used in the correction step of a homogenization procedure. The model accounts for short- and long-wave radiation fluxes (including a snow cover component for albedo calculation) of a measurement system, such as a radiation shield. One part of the flux is further modulated by ventilation. The model requires only cloud cover and wind speed for each day, but detailed site-specific information is necessary. The final model has three free parameters, one of which is a constant offset. The three parameters can be determined, e.g., using the mean offsets for three observation times. The model is developed using the example of the change from the Wild screen to the Stevenson screen in the temperature record of Basel, Switzerland, in 1966. It is evaluated based on parallel measurements of both systems during a sub-period at this location, which were discovered during the writing of this paper. The model can be used in the correction step of homogenization to distribute a known mean step-size to every single measurement, thus providing a reasonable alternative correction procedure for high-resolution historical climate series. It also constitutes an error model, which may be applied, e.g., in data assimilation approaches.

Centennial mineral dust variability in high-resolution ice core data from Dome C, Antarctica

Ice core data from Antarctica provide detailed insights into the characteristics of past climate, atmospheric circulation, as well as changes in the aerosol load of the atmosphere. We present high-resolution records of soluble calcium (Ca2+), non-sea-salt soluble calcium (nssCa2+), and particulate mineral dust aerosol from the East Antarctic Plateau at a depth resolution of 1 cm, spanning the past 800 000 years. Despite the fact that all three parameters are largely dust-derived, the ratio of nssCa2+ to particulate dust is dependent on the particulate dust concentration itself. We used principal component analysis to extract the joint climatic signal and produce a common high-resolution record of dust flux. This new record is used to identify Antarctic warming events during the past eight glacial periods. The phasing of dust flux and CO2 changes during glacial-interglacial transitions reveals that iron fertilization of the Southern Ocean during the past nine glacial terminations was not the dominant factor in the deglacial rise of CO2 concentrations. Rapid changes in dust flux during glacial terminations and Antarctic warming events point to a rapid response of the southern westerly wind belt in the region of southern South American dust sources on changing climate conditions. The clear lead of these dust changes on temperature rise suggests that an atmospheric reorganization occurred in the Southern Hemisphere before the Southern Ocean warmed significantly.

Histamine increases sphingosine kinase-1 expression and activity in the human arterial endothelial cell line EA.hy 926 by a PKC-alpha-dependent mechanism

Sphingosine 1-phosphate (S1P) is a potent mitogenic signal generated from sphingosine by the action of sphingosine kinases (SKs). In this study, we show that in the human arterial endothelial cell line EA.hy 926 histamine induces a time-dependent upregulation of the SK-1 mRNA and protein expression which is followed by increased SK-1 activity. A similar upregulation of SK-1 is also observed with the direct protein kinase C activator 12-O-tetradecanoylphorbol-13-acetate (TPA). In contrast, SK-2 activity is not affected by neither histamine nor TPA. The increased SK-1 protein expression is due to stimulated de novo synthesis since cycloheximide inhibited the delayed SK-1 protein upregulation. Moreover, the increased SK-1 mRNA expression results from an increased promoter activation by histamine and TPA. In mechanistic terms, the transcriptional upregulation of SK-1 is dependent on PKC and the extracellular signal-regulated protein kinase (ERK) cascade since staurosporine and the MEK inhibitor U0126 abolish the TPA-induced SK-1 induction. Furthermore, the histamine effect is abolished by the H1-receptor antagonist diphenhydramine, but not by the H2-receptor antagonist cimetidine. Parallel to the induction of SK-1, histamine and TPA stimulate an increased migration of endothelial cells, which is prevented by depletion of the SK-1 by small interfering RNA (siRNA). To appoint this specific cell response to a specific PKC isoenzyme, siRNA of PKC-alpha, -delta, and -epsilon were used to selectively downregulate the respective isoforms. Interestingly, only depletion of PKC-alpha leads to a complete loss of TPA- and histamine-triggered SK-1 induction and cell migration. In summary, these data show that PKC-alpha activation in endothelial cells by histamine-activated H1-receptors, or by direct PKC activators leads to a sustained upregulation of the SK-1 protein expression and activity which, in turn, is critically involved in the mechanism of endothelial cell migration.

Limited redundancy in phosphorylation of retinoblastoma tumor suppressor protein by cyclin-dependent kinases in acute lymphoblastic leukemia

Cyclin-dependent kinases (CDKs) successively phosphorylate the retinoblastoma protein (RB) at the restriction point in G1 phase. Hyperphosphorylation results in functional inactivation of RB, activation of the E2F transcriptional program, and entry of cells into S phase. RB unphosphorylated at serine 608 has growth suppressive activity. Phosphorylation of serines 608/612 inhibits binding of E2F-1 to RB. In Nalm-6 acute lymphoblastic leukemia extracts, serine 608 is phosphorylated by CDK4/6 complexes but not by CDK2. We reasoned that phosphorylation of serines 608/612 by redundant CDKs could accelerate phospho group formation and determined which G1 CDK contributes to serine 612 phosphorylation. Here, we report that CDK4 complexes from Nalm-6 extracts phosphorylated in vitro the CDK2-preferred serine 612, which was inhibited by p16INK4a, and fascaplysin. In contrast, serine 780 and serine 795 were efficiently phosphorylated by CDK4 but not by CDK2. The data suggest that the redundancy in phosphorylation of RB by CDK2 and CDK4 in Nalm-6 extracts is limited. Serine 612 phosphorylation by CDK4 also occurred in extracts of childhood acute lymphoblastic leukemia cells but not in extracts of mobilized CD34+ hemopoietic progenitor cells. This phenomenon could contribute to the commitment of childhood acute lymphocytic leukemia cells to proliferate and explain their refractoriness to differentiation-inducing agents.

Estimation with Interval Censored Data in Longitudinal Studies

In biostatistical applications interest often focuses on the estimation of the distribution of a time-until-event variable T. If one observes whether or not T exceeds an observed monitoring time at a random number of monitoring times, then the data structure is called interval censored data. We extend this data structure by allowing the presence of a possibly time-dependent covariate process that is observed until end of follow up. If one only assumes that the censoring mechanism satisfies coarsening at random, then, by the curve of dimensionality, typically no regular estimators will exist. To fight the curse of dimensionality we follow the approach of Robins and Rotnitzky (1992) by modeling parameters of the censoring mechanism. We model the right-censoring mechanism by modeling the hazard of the follow up time, conditional on T and the covariate process. For the monitoring mechanism we avoid modeling the joint distribution of the monitoring times by only modeling a univariate hazard of the pooled monitoring times, conditional on the follow up time, T, and the covariates process, which can be estimated by treating the pooled sample of monitoring times as i.i.d. In particular, it is assumed that the monitoring times and the right-censoring times only depend on T through the observed covariate process. We introduce inverse probability of censoring weighted (IPCW) estimator of the distribution of T and of smooth functionals thereof which are guaranteed to be consistent and asymptotically normal if we have available correctly specified semiparametric models for the two hazards of the censoring process. Furthermore, given such correctly specified models for these hazards of the censoring process, we propose a one-step estimator which will improve on the IPCW estimator if we correctly specify a lower-dimensional working model for the conditional distribution of T, given the covariate process, that remains consistent and asymptotically normal if this latter working model is misspecified. It is shown that the one-step estimator is efficient if each subject is at most monitored once and the working model contains the truth. In general, it is shown that the one-step estimator optimally uses the surrogate information if the working model contains the truth. It is not optimal in using the interval information provided by the current status indicators at the monitoring times, but simulations in Peterson, van der Laan (1997) show that the efficiency loss is small.

Locally Efficient Estimation with Current Status Data and High Dimensional Covariates

In biostatistical applications, interest often focuses on the estimation of the distribution of time T between two consecutive events. If the initial event time is observed and the subsequent event time is only known to be larger or smaller than an observed monitoring time, then the data is described by the well known singly-censored current status model, also known as interval censored data, case I. We extend this current status model by allowing the presence of a time-dependent process, which is partly observed and allowing C to depend on T through the observed part of this time-dependent process. Because of the high dimension of the covariate process, no globally efficient estimators exist with a good practical performance at moderate sample sizes. We follow the approach of Robins and Rotnitzky (1992) by modeling the censoring variable, given the time-variable and the covariate-process, i.e., the missingness process, under the restriction that it satisfied coarsening at random. We propose a generalization of the simple current status estimator of the distribution of T and of smooth functionals of the distribution of T, which is based on an estimate of the missingness. In this estimator the covariates enter only through the estimate of the missingness process. Due to the coarsening at random assumption, the estimator has the interesting property that if we estimate the missingness process more nonparametrically, then we improve its efficiency. We show that by local estimation of an optimal model or optimal function of the covariates for the missingness process, the generalized current status estimator for smooth functionals become locally efficient; meaning it is efficient if the right model or covariate is consistently estimated and it is consistent and asymptotically normal in general. Estimation of the optimal model requires estimation of the conditional distribution of T, given the covariates. Any (prior) knowledge of this conditional distribution can be used at this stage without any risk of losing root-n consistency. We also propose locally efficient one step estimators. Finally, we show some simulation results.

Locally Efficient Estimation in Censored Data Models: Theory and Examples

In many applications the observed data can be viewed as a censored high dimensional full data random variable X. By the curve of dimensionality it is typically not possible to construct estimators that are asymptotically efficient at every probability distribution in a semiparametric censored data model of such a high dimensional censored data structure. We provide a general method for construction of one-step estimators that are efficient at a chosen submodel of the full-data model, are still well behaved off this submodel and can be chosen to always improve on a given initial estimator. These one-step estimators rely on good estimators of the censoring mechanism and thus will require a parametric or semiparametric model for the censoring mechanism. We present a general theorem that provides a template for proving the desired asymptotic results. We illustrate the general one-step estimation methods by constructing locally efficient one-step estimators of marginal distributions and regression parameters with right-censored data, current status data and bivariate right-censored data, in all models allowing the presence of time-dependent covariates. The conditions of the asymptotics theorem are rigorously verified in one of the examples and the key condition of the general theorem is verified for all examples.

A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor

Boston Harbor has had a history of poor water quality, including contamination by enteric pathogens. We conduct a statistical analysis of data collected by the Massachusetts Water Resources Authority (MWRA) between 1996 and 2002 to evaluate the effects of court-mandated improvements in sewage treatment. Motivated by the ineffectiveness of standard Poisson mixture models and their zero-inflated counterparts, we propose a new negative binomial model for time series of Enterococcus counts in Boston Harbor, where nonstationarity and autocorrelation are modeled using a nonparametric smooth function of time in the predictor. Without further restrictions, this function is not identifiable in the presence of time-dependent covariates; consequently we use a basis orthogonal to the space spanned by the covariates and use penalized quasi-likelihood (PQL) for estimation. We conclude that Enterococcus counts were greatly reduced near the Nut Island Treatment Plant (NITP) outfalls following the transfer of wastewaters from NITP to the Deer Island Treatment Plant (DITP) and that the transfer of wastewaters from Boston Harbor to the offshore diffusers in Massachusetts Bay reduced the Enterococcus counts near the DITP outfalls.

Mixture Cure Survival Models with Dependent Censoring

A number of authors have studies the mixture survival model to analyze survival data with nonnegligible cure fractions. A key assumption made by these authors is the independence between the survival time and the censoring time. To our knowledge, no one has studies the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model which allows for dependent censoring. In particular, we derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection, and the two-sample comparison of latency distribution in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results using the martingale theory are obtained. We applied the proposed methodologies to the SEER prostate cancer data.

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods.