The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study

This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes

Estrogen protects the blood–brain barrier from inflammation-induced disruption and increased lymphocyte trafficking

Sex differences have been widely reported in neuroinflammatory disorders, focusing on the contributory role of estrogen. The microvascular endothelium of the brain is a critical component of the blood–brain barrier (BBB) and it is recognized as a major interface for communication between the periphery and the brain. As such, the cerebral capillary endothelium represents an important target for the peripheral estrogen neuroprotective functions, leading us to hypothesize that estrogen can limit BBB breakdown following the onset of peripheral inflammation. Comparison of male and female murine responses to peripheral LPS challenge revealed a short-term inflammation-induced deficit in BBB integrity in males that was not apparent in young females, but was notable in older, reproductively senescent females. Importantly, ovariectomy and hence estrogen loss recapitulated an aged phenotype in young females, which was reversible upon estradiol replacement. Using a well-established model of human cerebrovascular endothelial cells we investigated the effects of estradiol upon key barrier features, namely paracellular permeability, transendothelial electrical resistance, tight junction integrity and lymphocyte transmigration under basal and inflammatory conditions, modeled by treatment with TNFα and IFNγ. In all cases estradiol prevented inflammation-induced defects in barrier function, action mediated in large part through up-regulation of the central coordinator of tight junction integrity, annexin A1. The key role of this protein was then further confirmed in studies of human or murine annexin A1 genetic ablation models. Together, our data provide novel mechanisms for the protective effects of estrogen, and enhance our understanding of the beneficial role it plays in neurovascular/neuroimmune disease

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research

Miocene waterfowl and other birds from central Otago, New Zealand

Copyright © The Natural History Museum 2007Abundant fossil bird bones from the lower Bannockburn Formation, Manuherikia Group, an Early-Middle Miocene lacustrine deposit, 16–19 Ma, from Otago in New Zealand, reveal the “St Bathans Fauna” (new name), a first Tertiary avifauna of land and freshwater birds from New Zealand. At least 23 species of birds are represented by bones, and probable moa, Aves: Dinornithiformes, by eggshell. Anatids dominate the fauna with four genera and five species described as new: a sixth and largest anatid species is represented by just one bone. This is the most diverse Early-Middle Miocene duck fauna known worldwide. Among ducks, two species of dendrochenines are most numerous in the fauna, but a tadornine is common as well. A diving petrel (Pelecanoididae: Pelecanoides) is described, so extending the geological range of this genus worldwide from the Pliocene to the Middle Miocene, at least. The remaining 16 taxa are left undescribed but include: a large species of gull (Laridae); two small waders (Charadriiformes, genus indet.), the size of Charadrius bicinctus and Calidris ruficollis, respectively; a gruiform represented by one specimen similar to Aptornis; abundant rail (Rallidae) bones, including a common flightless rail and a rarer slightly larger taxon, about the size of Gallirallus philippensis; an ?eagle (Accipitridae); a pigeon (Columbidae); three parrots (Psittacidae); an owlet nightjar (Aegothelidae: Aegotheles sp.); a swiftlet (Apodidae: Collocalia sp.); and three passerine taxa, of which the largest is a member of the Cracticidae. The absence of some waterbirds, such as anserines (including swans), grebes (Podicipedidae) and shags (Phalacrocoracidae), among the abundant bones, indicates their probable absence from New Zealand in the Early-Middle Miocene.T. H. Worthy, A. J. D. Tennyson, C. Jones, J. A. McNamara and B. J. Dougla

The impact of B1+ correction on MP2RAGE cortical T1 and apparent cortical thickness at 7T

Determination of cortical thickness using MRI has often been criticized due to the presence of various error sources. Specifically, anatomical MRI relying on T1 contrast may be unreliable due to spatially variable image contrast between gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Especially at ultra-high field (≥ 7T) MRI, transmit and receive B1 -related image inhomogeneities can hamper correct classification of tissue types. In the current paper, we demonstrate that residual B1+ (transmit) inhomogeneities in the T1 -weighted and quantitative T1 images using the MP2RAGE sequence at 7T lead to biases in cortical thickness measurements. As expected, post-hoc correction for the spatially varying B1+ profile reduced the apparent T1 values across the cortex in regions with low B1+, and slightly increased apparent T1 in regions with high B1+. As a result, improved contrast-to-noise ratio both at the GM-CSF and GM-WM boundaries can be observed leading to more accurate surface reconstructions and cortical thickness estimates. Overall, the changes in cortical thickness ranged between a 5% decrease to a 70% increase after B1+ correction, reducing the variance of cortical thickness values across the brain dramatically and increasing the comparability with normative data. More specifically, the cortical thickness estimates increased in regions characterized by a strong decrease of apparent T1 after B1+ correction in regions with low B1+ due to improved detection of the pial surface. The current results suggest that cortical thickness can be more accurately determined using MP2RAGE data at 7T if B1+ inhomogeneities are accounted for

Reproducibility and Reliability of Quantitative and Weighted T1 and T2∗ Mapping for Myelin-Based Cortical Parcellation at 7 Tesla

Different magnetic resonance (MR) parameters, such as R1 (= 1/T1) or T2*, have been used to visualize non-invasively the myelin distribution across the cortical sheet. Myelin contrast is consistently enhanced in the primary sensory and some higher order cortical areas (such as MT or the cingulate cortex), which renders it suitable for subject-specific anatomical cortical parcellation. However, no systematic comparison has been performed between the previously proposed MR parameters, i.e. the longitudinal and transversal relaxation values (or their ratios), for myelin mapping at 7 Tesla. In addition, usually these MR parameters are acquired in a non-quantitative manner (weighted parameters). Here, we evaluated the differences in ‘parcellability’, contrast-to-noise ratio (CNR) and inter- and intra-subject variability and reproducibility, respectively, between high-resolution cortical surface maps based on these weighted MR parameters and their quantitative counterparts in ten healthy subjects. All parameters were obtained in a similar acquisition time and possible transmit- or receive-biases were removed during post-processing. It was found that CNR per unit time and parcellability were lower for the transversal compared to the longitudinal relaxation parameters. Further, quantitative R1 was characterized by the lowest inter- and intra-subject coefficient of variation (5.53% and 1.63%, respectively), making R1 a better parameter to map the myelin distribution compared to the other parameters. Moreover, quantitative MRI approaches offer the advantage of absolute rather than relative characterization of the underlying biochemical composition of the tissue, allowing more reliable comparison within subjects and between healthy subjects and patients. Finally, we explored two parcellation methods (thresholding the MR parameter values vs. surface gradients of these values) to determine areal borders based on the cortical surface pattern. It is shown that both methods are partially observer-dependent, needing manual interaction (i.e. choice of threshold or connecting high gradient values) to provide unambiguous borders

Optimization of Nested Queries in a Distributed Relational Database ABSTRACT

This paper describes how nested queries in the SQL language are processed by R*, an experimental adaptation to the distributed environment of the well-known centralized relational DBMS, System R. Nested queries are queries in which a predicate references the result of another query block (SELECT...FROM...WHERE...), called a subquery block (subQB). SubQBs may themselves contain one or more subQBs. Depending upon whether a subQB references values in other query blocks, it is processed differently, as either an Evaluate-at-Open or Evaluate-at-Application subQB type. Three tasks comprise execution of each query block: initiation, evaluation, and application. When the query’s tables are distributed among multiple sites, optimization of nested queries requires determining for each subQB: the site to perform each task, the protocols control-ling interactions between those tasks, and the costs of each option, so that a minimal-cost plan can be chosen. R * optimizes each query block independently, “bottom up”, using only the cost, cardinal&y, and result site of the subQB in the optimization of its containing query block. 1