Comparison of climate field reconstruction techniques: Application to Europe

This paper presents a comparison of principal component (PC) regression and regularized expectation maximization (RegEM) to reconstruct European summer and winter surface air temperature over the past millennium. Reconstruction is performed within a surrogate climate using the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) 1.4 and the climate model ECHO-G 4, assuming different white and red noise scenarios to define the distortion of pseudoproxy series. We show how sensitivity tests lead to valuable “a priori” information that provides a basis for improving real world proxy reconstructions. Our results emphasize the need to carefully test and evaluate reconstruction techniques with respect to the temporal resolution and the spatial scale they are applied to. Furthermore, we demonstrate that uncertainties inherent to the predictand and predictor data have to be more rigorously taken into account. The comparison of the two statistical techniques, in the specific experimental setting presented here, indicates that more skilful results are achieved with RegEM as low frequency variability is better preserved. We further detect seasonal differences in reconstruction skill for the continental scale, as e.g. the target temperature average is more adequately reconstructed for summer than for winter. For the specific predictor network given in this paper, both techniques underestimate the target temperature variations to an increasing extent as more noise is added to the signal, albeit RegEM less than with PC regression. We conclude that climate field reconstruction techniques can be improved and need to be further optimized in future applications.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Expectation Conditional Maximization-Based Deformable Shape Registration

This paper addresses the issue of matching statistical and non-rigid shapes, and introduces an Expectation Conditional Maximization-based deformable shape registration (ECM-DSR) algorithm. Similar to previous works, we cast the statistical and non-rigid shape registration problem into a missing data framework and handle the unknown correspondences with Gaussian Mixture Models (GMM). The registration problem is then solved by fitting the GMM centroids to the data. But unlike previous works where equal isotropic covariances are used, our new algorithm uses heteroscedastic covariances whose values are iteratively estimated from the data. A previously introduced virtual observation concept is adopted here to simplify the estimation of the registration parameters. Based on this concept, we derive closed-form solutions to estimate parameters for statistical or non-rigid shape registrations in each iteration. Our experiments conducted on synthesized and real data demonstrate that the ECM-DSR algorithm has various advantages over existing algorithms.

'Alternate-goal bias' in antisaccades and the influence of expectation

Saccadic performance depends on the requirements of the current trial, but also may be influenced by other trials in the same experiment. This effect of trial context has been investigated most for saccadic error rate and reaction time but seldom for the positional accuracy of saccadic landing points. We investigated whether the direction of saccades towards one goal is affected by the location of a second goal used in other trials in the same experimental block. In our first experiment, landing points ('endpoints') of antisaccades but not prosaccades were shifted towards the location of the alternate goal. This spatial bias decreased with increasing angular separation between the current and alternative goals. In a second experiment, we explored whether expectancy about the goal location was responsible for the biasing of the saccadic endpoint. For this, we used a condition where the saccadic goal randomly changed from one trial to the next between locations on, above or below the horizontal meridian. We modulated the prior probability of the alternate-goal location by showing cues prior to stimulus onset. The results showed that expectation about the possible positions of the saccadic goal is sufficient to bias saccadic endpoints and can account for at least part of this phenomenon of 'alternate-goal bias'.

ECM versus ICP for point registration

Iterative Closest Point (ICP) is a widely exploited method for point registration that is based on binary point-to-point assignments, whereas the Expectation Conditional Maximization (ECM) algorithm tries to solve the problem of point registration within the framework of maximum likelihood with point-to-cluster matching. In this paper, by fulfilling the implementation of both algorithms as well as conducting experiments in a scenario where dozens of model points must be registered with thousands of observation points on a pelvis model, we investigated and compared the performance (e.g. accuracy and robustness) of both ICP and ECM for point registration in cases without noise and with Gaussian white noise. The experiment results reveal that the ECM method is much less sensitive to initialization and is able to achieve more consistent estimations of the transformation parameters than the ICP algorithm, since the latter easily sinks into local minima and leads to quite different registration results with respect to different initializations. Both algorithms can reach the high registration accuracy at the same level, however, the ICP method usually requires an appropriate initialization to converge globally. In the presence of Gaussian white noise, it is observed in experiments that ECM is less efficient but more robust than ICP.

CX3CR1 defines functionally distinct intestinal mononuclear phagocyte subsets which maintain their respective functions during homeostatic and inflammatory conditions

Intestinal mononuclear phagocytes (iMNP) are critically involved in mucosal immunity and tissue homeostasis. Two major non-overlapping populations of iMNP have been identified in mice. CD103(+) iMNP represent a migratory population capable of inducing tolerogenic responses, whereas CX3CR1(+) iMNP are resident cells with disease-promoting potential. CX3CR1(+) iMNP can further be subdivided based on differential expression of CX3CR1. Using CX3CR1(GFP/+) ×RAG2(-/-) mice, we demonstrate that CX3CR1(hi) and CX3CR1(lo) iMNP clearly differ with respect to their morphological and functional properties. Compared with CX3CR1(hi) iMNP, CX3CR1(lo) iMNP are polarised towards pro-inflammatory responses already under homeostatic conditions. During a CD4(+) T-cell-induced colitis, CX3CR1(lo) cells accumulate in the inflamed mucosa and upregulate the expression of pro-inflammatory cytokines and triggering receptor expressed on myeloid cells-1 (TREM-1). In contrast, CX3CR1(hi) iMNP retain their non-inflammatory profile even during intestinal inflammation. These findings identify two functionally distinct iMNP subsets based on differential expression of CX3CR1 and indicate an unanticipated stability of iMNP.

Novel agents targeting the IGF-1R/PI3K pathway impair cell proliferation and survival in subsets of medulloblastoma and neuroblastoma

The receptor tyrosine kinase (RTK)/phosphoinositide 3-kinase (PI3K) pathway is fundamental for cancer cell proliferation and is known to be frequently altered and activated in neoplasia, including embryonal tumors. Based on the high frequency of alterations, targeting components of the PI3K signaling pathway is considered to be a promising therapeutic approach for cancer treatment. Here, we have investigated the potential of targeting the axis of the insulin-like growth factor-1 receptor (IGF-1R) and PI3K signaling in two common cancers of childhood: neuroblastoma, the most common extracranial tumor in children and medulloblastoma, the most frequent malignant childhood brain tumor. By treating neuroblastoma and medulloblastoma cells with R1507, a specific humanized monoclonal antibody against the IGF-1R, we could observe cell line-specific responses and in some cases a strong decrease in cell proliferation. In contrast, targeting the PI3K p110α with the specific inhibitor PIK75 resulted in broad anti-proliferative effects in a panel of neuro- and medulloblastoma cell lines. Additionally, sensitization to commonly used chemotherapeutic agents occurred in neuroblastoma cells upon treatment with R1507 or PIK75. Furthermore, by studying the expression and phosphorylation state of IGF-1R/PI3K downstream signaling targets we found down-regulated signaling pathway activation. In addition, apoptosis occurred in embryonal tumor cells after treatment with PIK75 or R1507. Together, our studies demonstrate the potential of targeting the IGF-1R/PI3K signaling axis in embryonal tumors. Hopefully, this knowledge will contribute to the development of urgently required new targeted therapies for embryonal tumors.

Single-cell analysis divides bovine monocyte-derived dendritic cells into subsets expressing either high or low levels of inducible nitric oxide synthase

Dendritic cells (DC) are important cells at the interface between innate and adaptive immunity. DC have a key role in antigen processing and presentation to T cells. Effector functions of DC related to innate immunity have not been explored extensively. We show that bovine monocyte-derived DC (mDC) express inducible nitric oxide synthase (iNOS) mRNA and protein and produce NO upon triggering with interferon-gamma (IFN-gamma) and heat-killed Listeria monocytogenes (HKLM). An immunocytochemical analysis revealed that a sizeable subset (20-60%) copiously expresses iNOS (iNOShi) upon IFN-gamma/HKLM triggering, whereas the other subset expressed low levels of iNOS (iNOSlo). Monocyte-derived macrophages (mMphi) are more homogeneous with regard to iNOS expression. The number of cells within the iNOSlo mDC subset is considerably larger than the number of dead cells or cells unresponsive to IFN-gamma/HKLM. The large majority of cells translocated p65 to the nucleus upon triggering by IFN-gamma/HKLM. A contamination of mDC with iNOS-expressing mMphi was excluded as follows. (i) Cell surface marker analysis suggested that mDC were relatively homogeneous, and no evidence for a contaminating subset expressing macrophage markers (e.g. high levels of CD14) was obtained. (ii) iNOS expression was stronger in iNOShi mDC than in mMphi. The use of maturation-promoting stimuli revealed only subtle phenotypic differences between immature and mature DC in cattle. Nevertheless, these stimuli promoted development of considerably fewer iNOShi mDC upon triggering with IFN-gamma/HKLM. Immunocytochemical results showed that although a significant proportion of cells expressed iNOS only or TNF only upon triggering with IFN-gamma/HKLM, a significant number of cells expressed both iNOS and TNF, suggesting that TNF and iNOS producing (TIP) DC are present within bovine mDC populations obtained in vitro.

Effects of expectation and caffeine on arousal, well-being, and reaction time

The objective of this study is to determine the impact of expectation associated with placebo and caffeine ingestion. We used a three-armed, randomized, double-blind design. Two three-armed experiments varying instruction (true, false, control) investigated the role of expectations of changes in arousal (blood pressure, heart rate), subjective well-being, and reaction time (RT). In Experiment 1 (N = 45), decaffeinated coffee was administered, and expectations were produced in one group by making them believe they had ingested caffeinated coffee. In Experiment 2 (N = 45), caffeinated orange juice was given in both experimental groups, but only one was informed about the true content. In Experiment 1, a significant effect for subjective alertness was found in the placebo treatment compared to the control group. However, for RT and well-being no significant effects were found. In Experiment 2, no significant expectancy effects were found. Caffeine produced large effects for blood pressure in both treatments compared to the control group, but the effects were larger for the false information group. For subjective well-being (alertness, calmness), considerable but nonsignificant changes were found for correctly informed participants, indicating possible additivity of pharmacologic effect and expectations. The results tentatively indicate that placebo and expectancy effects primarily show through introspection.

Telomere length in human natural killer cell subsets

Natural killer (NK) cells are cytotoxic cells that play a critical role in the innate immune response against infections and tumors. In the elderly, the cytotoxic function of NK cells is often compromised. Telomeres progressively shorten with each cell division and with age in most somatic cells eventually leading to chromosomal instability and cellular senescence. We studied the telomere length in NK cell subsets isolated from peripheral blood using "flow FISH," a method in which the hybridization of telomere probe in cells of interest is measured relative to internal controls in the same tube. We found that the average telomere length in human NK cells decreased with age as was previously found for human T lymphocytes. Separation of adult NK cells based on CD56 and CD16 expression revealed that the telomere length was significantly shorter in CD56(dim)CD16(+) (mature) NK cells compared to CD56(bright)CD16(-) (immature) NK cells from the same donor. Furthermore, sorting of NK cells based on expression of activation markers, such as NKG2D and LFA-1, revealed that NK cells expressing these markers have significantly shorter telomeres. Telomere fluorescence was very heterogeneous in NK cells expressing CD94, killer inhibitory receptor (KIR), NKG2A, or CD161. Our observations indicate that telomeric DNA in NK cells is lost with cell division and with age similar to what has been observed for most other hematopoietic cells. Telomere attrition in NK cells is a plausible cause for diminished NK cell function in the elderly.