Deficiency of RAMP1 Attenuates Antigen-Induced Airway Hyperresponsiveness in Mice

Asthma is a chronic inflammatory disease affecting the lung, characterized by breathing difficulty during an attack following exposure to an environmental trigger. Calcitonin gene-related peptide (CGRP) is a neuropeptide that may have a pathological role in asthma. The CGRP receptor is comprised of two components, which include the G-protein coupled receptor, calcitonin receptor-like receptor (CLR), and receptor activity-modifying protein 1 (RAMP1). RAMPs, including RAMP1, mediate ligand specificity in addition to aiding in the localization of receptors to the cell surface. Since there has been some controversy regarding the effect of CGRP on asthma, we sought to determine the effect of CGRP signaling ablation in an animal model of asthma. Using gene-targeting techniques, we generated mice deficient for RAMP1 by excising exon 3. After determining that these mice are viable and overtly normal, we sensitized the animals to ovalbumin prior to assessing airway resistance and inflammation after methacholine challenge. We found that mice lacking RAMP1 had reduced airway resistance and inflammation compared to wildtype animals. Additionally, we found that a 50% reduction of CLR, the G-protein receptor component of the CGRP receptor, also ameliorated airway resistance and inflammation in this model of allergic asthma. Interestingly, the loss of CLR from the smooth muscle cells did not alter the airway resistance, indicating that CGRP does not act directly on the smooth muscle cells to drive airway hyperresponsiveness. Together, these data indicate that signaling through RAMP1 and CLR plays a role in mediating asthma pathology. Since RAMP1 and CLR interact to form a receptor for CGRP, our data indicate that aberrant CGRP signaling, perhaps on lung endothelial and inflammatory cells, contributes to asthma pathophysiology. Finally, since RAMP-receptor interfaces are pharmacologically tractable, it may be possible to develop compounds targeting the RAMP1/CLR interface to assist in the treatment of asthma

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Boundaries of Semantic Distraction: Dominance and Lexicality Act at Retrieval

Three experiments investigated memory for semantic information with the goal of determining boundary conditions for the manifestation of semantic auditory distraction. Irrelevant speech disrupted the free recall of semantic category-exemplars to an equal degree regardless of whether the speech coincided with presentation or test phases of the task (Experiment 1) and occurred regardless of whether it comprised random words or coherent sentences (Experiment 2). The effects of background speech were greater when the irrelevant speech was semantically related to the to-be-remembered material, but only when the irrelevant words were high in output dominance (Experiment 3). The implications of these findings in relation to the processing of task material and the processing of background speech is discussed

Disruption of the Autophagy-Lysosome Pathway Is Involved in Neuropathology of the nclf Mouse Model of Neuronal Ceroid Lipofuscinosis

Variant late-infantile neuronal ceroid lipofuscinosis, a fatal lysosomal storage disorder accompanied by regional atrophy and pronounced neuron loss in the brain, is caused by mutations in the CLN6 gene. CLN6 is a non-glycosylated endoplasmic reticulum (ER)-resident membrane protein of unknown function. To investigate mechanisms contributing to neurodegeneration in CLN6 disease we examined the nclf mouse, a naturally occurring model of the human CLN6 disease. Prominent autofluorescent and electron-dense lysosomal storage material was found in cerebellar Purkinje cells, thalamus, hippocampus, olfactory bulb and in cortical layer II to V. Another prominent early feature of nclf pathogenesis was the localized astrocytosis that was evident in many brain regions and the more widespread microgliosis. Expression analysis of mutant Cln6 found in nclf mice demonstrated synthesis of a truncated protein with a reduced half-life. Whereas the rapid degradation of the mutant Cln6 protein can be inhibited by proteasomal inhibitors, there was no evidence for ER stress or activation of the unfolded protein response in various brain areas during postnatal development. Age-dependent increases in LC3-II, ubiquitinated proteins, and neuronal p62-positive aggregates were observed, indicating a disruption of the autophagy-lysosome degradation pathway of proteins in brains of nclf mice, most likely due to defective fusion between autophagosomes and lysosomes. These data suggest that proteasomal degradation of mutant Cln6 is sufficient to prevent the accumulation of misfolded Cln6 protein, whereas lysosomal dysfunction impairs constitutive autophagy promoting neurodegeneration

The Response of Vocal Fold Fibroblasts and Mesenchymal Stromal Cells to Vibration

Illumination of cellular changes caused by mechanical forces present within the laryngeal microenvironment may well guide strategies for tissue engineering the vocal fold lamina propria. The purpose of this study was to compare the response of human vocal fold fibroblasts (hVFF) and bone marrow mesenchymal stem cells (BM-MSC) to vibratory stimulus. In order to study these effects, a bioreactor capable of vibrating two cell seeded substrates was developed. The cell seeded substrates contact each other as a result of the sinusoidal frequency, producing a motion similar to the movement of true vocal folds. Utilizing this bioreactor, hVFF and BM-MSC were subjected to 200 Hz vibration and 20% strain for 8 hours. Immunohistochemistry (Ki-67 and TUNEL) was performed to examine cell proliferation and apoptosis respectively, while semi-quantitative RT-PCR was used to assess extracellular matrix related gene expression. HVFF significantly proliferated (p = 0.011) when subjected to 200 Hz vibration and 20% strain, while BM-MSC did not (p = 1.0). A statistically significant increase in apoptosis of BM-MSC (p = 0.0402) was observed under the experimental conditions; however high cell viability (96%) was maintained. HVFF did not have significantly altered apoptosis (p = 0.7849) when subjected to vibration and strain. Semi-quantitative RT-PCR results show no significant differences in expression levels of collagen I (BM-MSC p = 0.1951, hVFF p = v0.3629), fibronectin (BM-MSC p = 0.1951, hVFF p = 0.2513), and TGF-β1 (BM-MSC p = 0.2534, hVFF p = 0.6029) between vibratory and static conditions in either cell type. Finally, smooth muscle actin mRNA was not present in either vibrated or static samples, indicating that no myofibroblast differentiation occurred for either cell type. Together, these results demonstrate that BM-MSC may be a suitable alternative to hVFF for vocal fold tissue engineering. Further investigation into a larger number of gene markers, protein levels, increased number of donors and vibratory conditions are warranted

Protective versus pathogenic anti-CD4 immunity: insights from the study of natural resistance to HIV infection

HIV-1 exposure causes several dramatic unbalances in the immune system homeostasis. Here, we will focus on the paradox whereby CD4 specific autoimmune responses, which are expected to contribute to the catastrophic loss of most part of the T helper lymphocyte subset in infected patients, may display the characteristics of an unconventional protective immunity in individuals naturally resistant to HIV-1 infection. Reference to differences in fine epitope mapping of these two oppositely polarized outcomes will be presented, with particular reference to partially or totally CD4-gp120 complex-specific antibodies. The fine tuning of the anti-self immune response to the HIV-1 receptor may determine whether viral exposure will result in infection or, alternatively, protective immunity

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders

Association of adiposity and mental health functioning across the lifespan:Findings from understanding society (The UK household longitudinal study)

Background: Evidence on the adiposity-mental health associations is mixed, with studies finding positive, negative or no associations, and less is known about how these associations may vary by age. Objective: To examine the association of adiposity -body mass index (BMI), waist circumference (WC) and percentage body fat (BF%)- with mental health functioning across the adult lifespan. Methods: Data from 11,257 participants (aged 18+) of Understanding Society: the UK Household Longitudinal Study (waves 2 and 3, 5/2010-7/2013) were employed. Regressions of mental health functioning, assessed by the Mental Component Summary (MCS-12) and the General Health Questionnaire (GHQ-12), on adiposity measures (continuous or dichotomous indicators) were estimated adjusted for covariates. Polynomial age-adiposity interactions were estimated. Results: Higher adiposity was associated with poorer mental health functioning. This emerged in the 30s, increased up to mid-40s (all central adiposity and obesity-BF% measures) or early 50s (all BMI measures) and then decreased with age. Underlying physical health generally accounted for these associations except for central adiposity, where associations remained statistically significant from the mid-30s to50s. Cardiovascular, followed by arthritis and endocrine, conditions played the greatest role in attenuating the associations under investigation. Conclusions: We found strong age-specific patterns in the adiposity-mental health functioning association that varied across adiposity measures. Underlying physical health had the dominant role in attenuating these associations. Policy makers and health professionals should target increased adiposity, mainly central adiposity, as it is a risk factor for poor mental health functioning in those aged between mid-30s to 50 years