1,338 research outputs found
M1 muscarinic allosteric modulators slow prion neurodegeneration and restore memory loss
This is the final version of the article. Available from American Society for Clinical Investigation via the DOI in this record.The current frontline symptomatic treatment for Alzheimerās disease (AD) is whole-body upregulation of cholinergic
transmission via inhibition of acetylcholinesterase. This approach leads to profound dose-related adverse effects. An
alternative strategy is to selectively target muscarinic acetylcholine receptors, particularly the M1 muscarinic acetylcholine
receptor (M1 mAChR), which was previously shown to have procognitive activity. However, developing M1 mAChRāselective orthosteric ligands has proven challenging. Here, we have shown that mouse prion disease shows many of the hallmarks
of human AD, including progressive terminal neurodegeneration and memory deficits due to a disruption of hippocampal
cholinergic innervation. The fact that we also show that muscarinic signaling is maintained in both AD and mouse prion
disease points to the latter as an excellent model for testing the efficacy of muscarinic pharmacological entities. The memory deficits we observed in mouse prion disease were completely restored by treatment with benzyl quinolone carboxylic acid (BQCA) and benzoquinazoline-12 (BQZ-12), two highly selective positive allosteric modulators (PAMs) of M1 mAChRs. Furthermore, prolonged exposure to BQCA markedly extended the lifespan of diseased mice. Thus, enhancing hippocampal muscarinic signaling using M1 mAChR PAMs restored memory loss and slowed the progression of mouse prion disease, indicating that this ligand type may have clinical benefit in diseases showing defective cholinergic transmission, such as AD.ABT, AC, and PMS received funding from a Wellcome Trust Collaborative
Award (201529/Z/16/Z). ABT, SJB, AJB, and TMH were
funded through a Medical Research Council programme leader
grant provided by the MRC Toxicology Unit. CCF, LMB, AJM, and
HES were funded by the Eli Lilly Company. JMB received funding
through a Lilly Research Award Program (LRAP) grant (Eli
Lilly). RP received funding from the Marie Curie grant āExtrabrainā
(European Commission). AC is a senior principal research
fellow and PMS a principal research fellow of the National Health
and Medical Research Council of Australia. Tissue samples were
from Randy Woltjer at the Oregon Alzheimerās Disease Center.
The Oregon Alzheimerās Disease Center is supported by NIH grant P30AG008017
Spatial and topological organization of DNA chains induced by gene co-localization
Transcriptional activity has been shown to relate to the organization of
chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In
particular, highly transcribed genes, RNA polymerases and transcription factors
gather into discrete spatial foci called transcription factories. However, the
mechanisms underlying the formation of these foci and the resulting topological
order of the chromosome remain to be elucidated. Here we consider a
thermodynamic framework based on a worm-like chain model of chromosomes where
sparse designated sites along the DNA are able to interact whenever they are
spatially close-by. This is motivated by recurrent evidence that there exists
physical interactions between genes that operate together. Three important
results come out of this simple framework. First, the resulting formation of
transcription foci can be viewed as a micro-phase separation of the interacting
sites from the rest of the DNA. In this respect, a thermodynamic analysis
suggests transcription factors to be appropriate candidates for mediating the
physical interactions between genes. Next, numerical simulations of the polymer
reveal a rich variety of phases that are associated with different topological
orderings, each providing a way to increase the local concentrations of the
interacting sites. Finally, the numerical results show that both
one-dimensional clustering and periodic location of the binding sites along the
DNA, which have been observed in several organisms, make the spatial
co-localization of multiple families of genes particularly efficient.Comment: Figures and Supplementary Material freely available on
http://dx.doi.org/10.1371/journal.pcbi.100067
The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.Methods: A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes ( birth weight, small for gestational age and preterm births), in a two-level hierarchical model.Results: We found effects of both individual ( education, race, prenatal care index) and area-based ( median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.Conclusion: Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.This work is supported by the Harvard Environmental Protection Agency (EPA) Center,
Grants R827353 and R-832416, and National Institute for Environmental Health Science (NIEHS) ES-0002
Fluorescent characterization of differentiated myotubes using flow cytometry
Flow cytometry is routinely used in the assessment of skeletal muscle progenitor cell (myoblast) populations. However, a full gating strategy, inclusive of difficult to interpret forward and side scatter data, which documents cytometric analysis of differentiated myoblasts (myotubes) has not been reported. Beyond changes in size and shape, there are substantial metabolic and protein changes in myotubes allowing for their potential identification within heterogenous cell suspensions. To establish the utility of flow cytometry for determination of myoblasts and myotubes, C2C12 murine cell populations were assessed for cell morphology and metabolic reprogramming. Laser scatter, both forward (FSC; size) and side (SSC; granularity), measured cell morphology, while mitochondrial mass, reactive oxygen species (ROS) generation and DNA content were quantified using the fluorescent probes, MitoTracker green, CM-H2DCFDA and Vybrant DyeCycle, respectively. Immunophenotyping for myosin heavy chain (MyHC) was utilized to confirm myotube differentiation. Cellular viability was determined using Annexin V/propidium iodide dual labelling. Fluorescent microscopy was employed to visualize fluorescence and morphology. Myotube and myoblast populations were resolvable through non-intuitive interpretation of laser scatter-based morphology assessment and mitochondrial mass and activity assessment. Myotubes appeared to have similar sizes to the myoblasts based on laser scatter but exhibited greater mitochondrial mass (159%, p < 0.0001), ROS production (303%, p < 0.0001), DNA content (18%, p < 0.001) and expression of MyHC (147%, p < 0.001) compared to myoblasts. Myotube sub-populations contained a larger viable cluster of cells which were unable to be fractionated from myoblast populations and a smaller population cluster which likely contains apoptotic bodies. Imaging of differentiated myoblasts that had transited through the flow cytometer revealed the presence of intact, ārolled-upā myotubes, which would alter laser scatter properties and potential transit through the laser beam. Our results indicate that myotubes can be analyzed successfully using flow cytometry. Increased mitochondrial mass, ROS and DNA content are key features that correlate with MyHC expression but due to myotubes ārolling upā during flow cytometric analysis, laser scatter determination of size is not positively correlated; a phenomenon observed with some size determination particles and related to surface properties of said particles. We also note a greater heterogeneity of myotubes compared to myoblasts as evidenced by the 2 distinct sub-populations. We suggest that acoustic focussing may prove effective in identifying myotube sub populations compared to traditional hydrodynamic focussing
Conscious monitoring and control (reinvestment) in surgical performance under pressure.
Research on intraoperative stressors has focused on external factors without considering individual differences in the ability to cope with stress. One individual difference that is implicated in adverse effects of stress on performance is "reinvestment," the propensity for conscious monitoring and control of movements. The aim of this study was to examine the impact of reinvestment on laparoscopic performance under time pressure
THG113.31, a specific PGF2alpha receptor antagonist, induces human myometrial relaxation and BKCa channel activation
BACKGROUND: PGF2alpha exerts a significant contractile effect on myometrium and is central to human labour. THG113.31, a specific non-competitive PGF2alpha receptor (FP) antagonist, exerts an inhibitory effect on myometrial contractility. The BKCa channel is ubiquitously encountered in human uterine tissue and plays a significant role in modulating myometrial cell membrane potential and excitability. The objective of this study was to investigate potential BKCa channel involvement in the response of human myometrium to THG113.31. METHODS: Single and whole-cell electrophysiological BKCa channel recordings from freshly dispersed myocytes, were investigated in the presence and absence of THG113.31. Functional studies investigated the effects of THG113.31 on isolated spontaneous myometrial contractions, in the presence and absence of the BKCa channel blocker, iberiotoxin. RESULTS: Single channel recordings identified the BKCa channel as a target of THG113.31. THG113.31 significantly increased the open state probability of these channels [control 0.023+/-0.006; 10 microM THG113.31 0.087+/-0.012 (P = 0.009); and 50 microM THG113.31 0.1356+/-0.018 (P = 0.001)]. In addition, THG113.31 increased whole-cell BKCa currents over a range of membrane potentials, and this effect was reversed by 100 nanoM IbTX. Isometric tension studies demonstrated that THG113.31 exerted a significant concentration-dependent relaxant effect on human myometrial tissue and pre-incubation of strips with IbTX abolished this effect on spontaneously occurring contractions. CONCLUSION: These data suggests that activation of the BKCa channel may contribute, at least partially, to the uterorelaxant effect of THG113.31
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Towards a typology for constrained climate model forecasts
In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context
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