Comparison of high-latitude thermospheric meridionalwinds I: optical and radar experimental comparisons

Thermospheric neutral winds at Kiruna, Sweden (67.4°N, 20.4°E) are compared using both direct optical Fabry-Perot Interferometer (FPI) measurements and those derived from European incoherent scatter radar (EISCAT) measurements. This combination of experimental data sets, both covering well over a solar cycle of data, allows for a unique comparison of the thermospheric meridional component of the neutral wind as observed by different experimental techniques. Uniquely in this study the EISCAT measurements are used to provide winds for comparison using two separate techniques: the most popular method based on the work of Salah and Holt (1974) and the Meridional Wind Model (MWM) (Miller et al., 1997) application of servo theory. The balance of forces at this location that produces the observed diurnal pattern are investigated using output from the Coupled Thermosphere and Ionosphere (CTIM) numerical model. Along with detailed comparisons from short periods the climatological behaviour of the winds have been investigated for seasonal and solar cycle dependence using the experimental techniques. While there are features which are consistent between the 3 techniques, such as the evidence of the equinoctial asymmetry, there are also significant differences between the techniques both in terms of trends and absolute values. It is clear from this and previous studies that the high-latitude representation of the thermospheric neutral winds from the empirical Horizontal Wind Model (HWM), though improved from earlier versions, lacks accuracy in many conditions. The relative merits of each technique are discussed and while none of the techniques provides the perfect data set to address model performance at high-latitude, one or more needs to be included in future HWM reformulations.<p> <b>Key words.</b> Meteorology and atmospheric dynamics (thermospheric dynamics), Ionosphere (ionosphere-atmosphere interactions, auroral ionosphere

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

The impact of induced anxiety on affective response inhibition

Studying the effects of experimentally induced anxiety in healthy volunteers may increase our understanding of the mechanisms underpinning anxiety disorders. Experimentally induced stress (via threat of unpredictable shock) improves accuracy at withholding a response on the sustained attention to response task (SART), and in separate studies improves accuracy to classify fearful faces, creating an affective bias. Integrating these findings, participants at two public science engagement events (n = 46, n = 55) were recruited to explore the effects of experimentally induced stress on an affective version of the SART. We hypothesized that we would see an improved accuracy at withholding a response to affectively congruent stimuli (i.e. increased accuracy at withholding a response to fearful 'no-go' distractors) under threat of shock. Induced anxiety slowed reaction time, and at the second event quicker responses were made to fearful stimuli. However, we did not observe improved inhibition overall during induced anxiety, and there was no evidence to suggest an interaction between induced anxiety and stimulus valence on response accuracy. Indeed Bayesian analysis provided decisive evidence against this hypothesis. We suggest that the presence of emotional stimuli might make the safe condition more anxiogenic, reducing the differential between conditions and knocking out any threat-potentiated improvement

A Locally Adaptive Regularization Based on Anisotropic Diffusion for Deformable Image Registration of Sliding Organs

We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall

Serum measures of hexabromocyclododecane (HBCDD) and polyborminated diphenyl ethers (PBDEs) in reproductive-aged women in the United Kingdom

We investigated the serum concentrations of two brominated flame retardants (BFRs) – polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCDD) –in 59 women aged between 23 and 42 from the United Kingdom. We also collected demographic data, including age, bodyweight and height in order to test for associations with BFR levels. Temporal and global differences were also assessed using previously published data.HBCDD was detected in 68% of samples with a mean concentration of 2.2 ng/g lipid (range =< 0.3–13 ng/g lipid). The dominant stereoisomer was α-HBCDD with an average contribution of 82% (0–100%) towards ΣHBCDD, was followed by γ-HBCDD (average contribution = 17%). PBDEs were detected in 95% of samples with a mean ∑PBDE (sum of BDEs −28, −47, −99, −100, −153, −154 and −183) concentration of 2.4 ng/g lipid (range = 2.5 since 2010. Whilst the human body burden appear to be decreasing, both PBDEs and HBCDD are still consistently detected in human serum, despite legislative action limiting their production and use. This highlights the need to continuously assess human exposure and the effectiveness of policy aimed at reducing exposure

Down syndrome-recent progress and future prospects

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and is associated with a number of deleterious phenotypes, including learning disability, heart defects, early-onset Alzheimer's disease and childhood leukaemia. Individuals with DS are affected by these phenotypes to a variable extent; understanding the cause of this variation is a key challenge. Here, we review recent research progress in DS, both in patients and relevant animal models. In particular, we highlight exciting advances in therapy to improve cognitive function in people with DS and the significant developments in understanding the gene content of Hsa21. Moreover, we discuss future research directions in light of new technologies. In particular, the use of chromosome engineering to generate new trisomic mouse models and large-scale studies of genotype-phenotype relationships in patients are likely to significantly contribute to the future understanding of DS

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction☆

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Diel transcriptional response of a California Current plankton microbiome to light, low iron, and enduring viral infection

Phytoplankton and associated microbial communities provide organic carbon to oceanic food webs and drive ecosystem dynamics. However, capturing those dynamics is challenging. Here, an in situ, semi-Lagrangian, robotic sampler profiled pelagic microbes at 4 h intervals over ~2.6 days in North Pacific high-nutrient, low-chlorophyll waters. We report on the community structure and transcriptional dynamics of microbes in an operationally large size class (>5 μm) predominantly populated by dinoflagellates, ciliates, haptophytes, pelagophytes, diatoms, cyanobacteria (chiefly Synechococcus), prasinophytes (chiefly Ostreococcus), fungi, archaea, and proteobacteria. Apart from fungi and archaea, all groups exhibited 24-h periodicity in some transcripts, but larger portions of the transcriptome oscillated in phototrophs. Periodic photosynthesis-related transcripts exhibited a temporal cascade across the morning hours, conserved across diverse phototrophic lineages. Pronounced silica:nitrate drawdown, a high flavodoxin to ferredoxin transcript ratio, and elevated expression of other Fe-stress markers indicated Fe-limitation. Fe-stress markers peaked during a photoperiodically adaptive time window that could modulate phytoplankton response to seasonal Fe-limitation. Remarkably, we observed viruses that infect the majority of abundant taxa, often with total transcriptional activity synchronized with putative hosts. Taken together, these data reveal a microbial plankton community that is shaped by recycled production and tightly controlled by Fe-limitation and viral activity