Homophilic Protocadherin Cell-Cell Interactions Promote Dendrite Complexity

SummaryGrowth of a properly complex dendrite arbor is a key step in neuronal differentiation and a prerequisite for neural circuit formation. Diverse cell surface molecules, such as the clustered protocadherins (Pcdhs), have long been proposed to regulate circuit formation through specific cell-cell interactions. Here, using transgenic and conditional knockout mice to manipulate γ-Pcdh repertoire in the cerebral cortex, we show that the complexity of a neuron’s dendritic arbor is determined by homophilic interactions with other cells. Neurons expressing only one of the 22 γ-Pcdhs can exhibit either exuberant or minimal dendrite complexity, depending only on whether surrounding cells express the same isoform. Furthermore, loss of astrocytic γ-Pcdhs, or disruption of astrocyte-neuron homophilic matching, reduces dendrite complexity cell non-autonomously. Our data indicate that γ-Pcdhs act locally to promote dendrite arborization via homophilic matching, and they confirm that connectivity in vivo depends on molecular interactions between neurons and between neurons and astrocytes

A positional statistic for 1324-avoiding permutations

We consider the class $S_n(1324)$ of permutations of size $n$ that avoid the pattern 1324 and examine the subset $S_n^{a\prec n}(1324)$ of elements for which $a\prec n\prec [a-1]$, $a\ge 1$. This notation means that, when written in one line notation, such a permutation must have $a$ to the left of $n$, and the elements of $\{1,\dots,a-1\}$ must all be to the right of $n$. For $n\ge 2$, we establish a connection between the subset of permutations in $S_n^{1\prec n}(1324)$ having the 1 adjacent to the $n$ (called primitives), and the set of 1324-avoiding dominoes with $n-2$ points. For $a\in\{1,2\}$, we introduce constructive algorithms and give formulas for the enumeration of $S_n^{a\prec n}(1324)$ by the position of $a$ relative to the position of $n$. For $a\ge 3$, we formulate some conjectures for the corresponding generating functions.Comment: 8 pages. Submitted for publicatio

Cerebral Amyloid and Hypertension are Independently Associated with White Matter Lesions in Elderly.

In cognitively normal (CN) elderly individuals, white matter hyperintensities (WMH) are commonly viewed as a marker of cerebral small vessel disease (SVD). SVD is due to exposure to systemic vascular injury processes associated with highly prevalent vascular risk factors (VRFs) such as hypertension, high cholesterol, and diabetes. However, cerebral amyloid accumulation is also prevalent in this population and is associated with WMH accrual. Therefore, we examined the independent associations of amyloid burden and VRFs with WMH burden in CN elderly individuals with low to moderate vascular risk. Participants (n = 150) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) received fluid attenuated inversion recovery (FLAIR) MRI at study entry. Total WMH volume was calculated from FLAIR images co-registered with structural MRI. Amyloid burden was determined by cerebrospinal fluid Aβ1-42 levels. Clinical histories of VRFs, as well as current measurements of vascular status, were recorded during a baseline clinical evaluation. We tested ridge regression models for independent associations and interactions of elevated blood pressure (BP) and amyloid to total WMH volume. We found that greater amyloid burden and a clinical history of hypertension were independently associated with greater WMH volume. In addition, elevated BP modified the association between amyloid and WMH, such that those with either current or past evidence of elevated BP had greater WMH volumes at a given burden of amyloid. These findings are consistent with the hypothesis that cerebral amyloid accumulation and VRFs are independently associated with clinically latent white matter damage represented by WMHs. The potential contribution of amyloid to WMHs should be further explored, even among elderly individuals without cognitive impairment and with limited VRF exposure

Kiloparsec-scale Spatial Offsets in Double-peaked Narrow-line Active Galactic Nuclei. I. Markers for Selection of Compelling Dual Active Galactic Nucleus Candidates

Merger-remnant galaxies with kpc-scale separation dual active galactic nuclei (AGNs) should be widespread as a consequence of galaxy mergers and triggered gas accretion onto supermassive black holes, yet very few dual AGNs have been observed. Galaxies with double-peaked narrow AGN emission lines in the Sloan Digital Sky Survey are plausible dual AGN candidates, but their double-peaked profiles could also be the result of gas kinematics or AGN-driven outflows and jets on small or large scales. To help distinguish between these scenarios, we have obtained spatial profiles of the AGN emission via follow-up long-slit spectroscopy of 81 double-peaked narrow-line AGNs in SDSS at 0.03 < z < 0.36 using Lick, Palomar, and MMT Observatories. We find that all 81 systems exhibit double AGN emission components with ~kpc projected spatial separations on the sky, which suggests that they are produced by kpc-scale dual AGNs or kpc-scale outflows, jets, or rotating gaseous disks. In addition, we find that the subsample (58%) of the objects with spatially compact emission components may be preferentially produced by dual AGNs, while the subsample (42%) with spatially extended emission components may be preferentially produced by AGN outflows. We also find that for 32% of the sample the two AGN emission components are preferentially aligned with the host galaxy major axis, as expected for dual AGNs orbiting in the host galaxy potential. Our results both narrow the list of possible physical mechanisms producing the double AGN components, and suggest several observational criteria for selecting the most promising dual AGN candidates from the full sample of double-peaked narrow-line AGNs. Using these criteria, we determine the 17 most compelling dual AGN candidates in our sample.Comment: 12 pages, 8 figures, published in ApJ. Modified from original version to reflect referee's comment

Medication decision-making for patients with renal insufficiency in inpatient and outpatient care at a US Veterans Affairs Medical Centre: a qualitative, cognitive task analysis.

BackgroundMany studies identify factors that contribute to renal prescribing errors, but few examine how healthcare professionals (HCPs) detect and recover from an error or potential patient safety concern. Knowledge of this information could inform advanced error detection systems and decision support tools that help prevent prescribing errors.ObjectiveTo examine the cognitive strategies that HCPs used to recognise and manage medication-related problems for patients with renal insufficiency.DesignHCPs submitted documentation about medication-related incidents. We then conducted cognitive task analysis interviews. Qualitative data were analysed inductively.SettingInpatient and outpatient facilities at a major US Veterans Affairs Medical Centre.ParticipantsPhysicians, nurses and pharmacists who took action to prevent or resolve a renal-drug problem in patients with renal insufficiency.OutcomesEmergent themes from interviews, as related to recognition of renal-drug problems and decision-making processes.ResultsWe interviewed 20 HCPs. Results yielded a descriptive model of the decision-making process, comprised of three main stages: detect, gather information and act. These stages often followed a cyclical path due largely to the gradual decline of patients' renal function. Most HCPs relied on being vigilant to detect patients' renal-drug problems rather than relying on systems to detect unanticipated cues. At each stage, HCPs relied on different cognitive cues depending on medication type: for renally eliminated medications, HCPs focused on gathering renal dosing guidelines, while for nephrotoxic medications, HCPs investigated the need for particular medication therapy, and if warranted, safer alternatives.ConclusionsOur model is useful for trainees so they can gain familiarity with managing renal-drug problems. Based on findings, improvements are warranted for three aspects of healthcare systems: (1) supporting the cyclical nature of renal-drug problem management via longitudinal tracking mechanisms, (2) providing tools to alleviate HCPs' heavy reliance on vigilance and (3) supporting HCPs' different decision-making needs for renally eliminated versus nephrotoxic medications

K-Bayes Reconstruction for Perfusion MRI I: Concepts and Application

Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. In this study, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach (described in detail in Part II: Modeling and Technical Development) combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT

Ultra-deep Large Binocular Camera U-band Imaging of the GOODS-North Field: Depth vs. Resolution

We present a study of the trade-off between depth and resolution using a large number of U-band imaging observations in the GOODS-North field (Giavalisco et al. 2004) from the Large Binocular Camera (LBC) on the Large Binocular Telescope (LBT). Having acquired over 30 hours of data (315 images with 5-6 mins exposures), we generated multiple image mosaics, starting with the best atmospheric seeing images (FWHM $\lesssim$0.8"), which constitute $\sim$10% of the total data set. For subsequent mosaics, we added in data with larger seeing values until the final, deepest mosaic included all images with FWHM $\lesssim$1.8" ($\sim$94% of the total data set). From the mosaics, we made object catalogs to compare the optimal-resolution, yet shallower image to the lower-resolution but deeper image. We show that the number counts for both images are $\sim$90% complete to $U_{AB}$ $\lesssim26$. Fainter than $U_{AB}$$\sim$ 27, the object counts from the optimal-resolution image start to drop-off dramatically (90% between $U_{AB}$ = 27 and 28 mag), while the deepest image with better surface-brightness sensitivity ($\mu^{AB}_{U}$$\lesssim$ 32 mag arcsec$^{-2}$) show a more gradual drop (10% between $U_{AB}$ $\simeq$ 27 and 28 mag). For the brightest galaxies within the GOODS-N field, structure and clumpy features within the galaxies are more prominent in the optimal-resolution image compared to the deeper mosaics. Finally, we find - for 220 brighter galaxies with $U_{AB}$$\lesssim$ 24 mag - only marginal differences in total flux between the optimal-resolution and lower-resolution light-profiles to $\mu^{AB}_{U}$$\lesssim$ 32 mag arcsec$^{-2}$. In only 10% of the cases are the total-flux differences larger than 0.5 mag. This helps constrain how much flux can be missed from galaxy outskirts, which is important for studies of the Extragalactic Background Light.Comment: 24 pages, 14 figures, submitted to PASP, comments welcom