316 research outputs found
Human Embryonic Stem Cells Express Elevated Levels of Multiple Pro-Apoptotic BCL-2 Family Members
Two of the greatest challenges in regenerative medicine today remain (1) the ability to culture human embryonic stem cells (hESCs) at a scale sufficient to satisfy clinical demand and (2) the ability to eliminate teratoma-forming cells from preparations of cells with clinically desirable phenotypes. Understanding the pathways governing apoptosis in hESCs may provide a means to address these issues. Limiting apoptosis could aid scaling efforts, whereas triggering selective apoptosis in hESCs could eliminate unwanted teratoma-forming cells. We focus here on the BCL-2 family of proteins, which regulate mitochondrial-dependent apoptosis. We used quantitative PCR to compare the steady-state expression profile of all human BCL-2 family members in hESCs with that of human primary cells from various origins and two cancer lines. Our findings indicate that hESCs express elevated levels of the pro-apoptotic BH3-only BCL-2 family members NOXA, BIK, BIM, BMF and PUMA when compared with differentiated cells and cancer cells. However, compensatory expression of pro-survival BCL-2 family members in hESCs was not observed, suggesting a possible explanation for the elevated rates of apoptosis observed in proliferating hESC cultures, as well as a mechanism that could be exploited to limit hESC-derived neoplasms
Recommended from our members
A mechanistic spatio-temporal framework for modelling individual-to-individual transmissionâWith an application to the 2014-2015 West Africa Ebola outbreak
In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging
Endothelial Stomatal and Fenestral Diaphragms in Normal Vessels and Angiogenesis
Vascular endothelium lines the entire cardiovascular system where performs a series of vital functions including the control of microvascular permeability, coagulation inflammation, vascular tone as well as the formation of new vessels via vasculogenesis and angiogenesis in normal and disease states. Normal endothelium consists of heterogeneous populations of cells differentiated according to the vascular bed and segment of the vascular tree where they occur. One of the cardinal features is the expression of specific subcellular structures such as plasmalemmal vesicles or caveolae, transendothelial channels, vesiculo-vacuolar organelles, endothelial pockets and fenestrae, whose presence define several endothelial morphological types. A less explored observation is the differential expression of such structures in diverse settings of angiogenesis. This review will focus on the latest developments on the components, structure and function of these specific endothelial structures in normal endothelium as well as in diverse settings of angiogenesis
Computational Design of a PDZ Domain Peptide Inhibitor that Rescues CFTR Activity
The cystic fibrosis transmembrane conductance regulator (CFTR) is an epithelial chloride channel mutated in patients with cystic fibrosis (CF). The most prevalent CFTR mutation, ÎF508, blocks folding in the endoplasmic reticulum. Recent work has shown that some ÎF508-CFTR channel activity can be recovered by pharmaceutical modulators (âpotentiatorsâ and âcorrectorsâ), but ÎF508-CFTR can still be rapidly degraded via a lysosomal pathway involving the CFTR-associated ligand (CAL), which binds CFTR via a PDZ interaction domain. We present a study that goes from theory, to new structure-based computational design algorithms, to computational predictions, to biochemical testing and ultimately to epithelial-cell validation of novel, effective CAL PDZ inhibitors (called âstabilizersâ) that rescue ÎF508-CFTR activity. To design the âstabilizersâ, we extended our structural ensemble-based computational protein redesign algorithm to encompass protein-protein and protein-peptide interactions. The computational predictions achieved high accuracy: all of the top-predicted peptide inhibitors bound well to CAL. Furthermore, when compared to state-of-the-art CAL inhibitors, our design methodology achieved higher affinity and increased binding efficiency. The designed inhibitor with the highest affinity for CAL (kCAL01) binds six-fold more tightly than the previous best hexamer (iCAL35), and 170-fold more tightly than the CFTR C-terminus. We show that kCAL01 has physiological activity and can rescue chloride efflux in CF patient-derived airway epithelial cells. Since stabilizers address a different cellular CF defect from potentiators and correctors, our inhibitors provide an additional therapeutic pathway that can be used in conjunction with current methods
Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation
There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity
Search for anomalous couplings in the W tb vertex from the measurement of double differential angular decay rates of single top quarks produced in the t-channel with the ATLAS detector
The electroweak production and subsequent decay of single top quarks is determined by the properties of the Wtb vertex. This vertex can be described by the complex parameters of an effective Lagrangian. An analysis of angular distributions of the decay products of single top quarks produced in the t -channel constrains these parameters simultaneously. The analysis described in this paper uses 4.6 fbâ1 of proton-proton collision data at âs =7 TeV collected with the ATLAS detector at the LHC. Two parameters are measured simultaneously in this analysis. The fraction f 1 of decays containing transversely polarised W bosons is measured to be 0.37 ± 0.07 (stat.âsyst.). The phase ÎŽ â between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be â0.014Ï Â± 0.036Ï (stat.âsyst.). The correlation in the measurement of these parameters is 0.15. These values result in two-dimensional limits at the 95% confidence level on the ratio of the complex coupling parameters g R and V L, yielding Re[g R /V L] â [â0.36, 0.10] and Im[g R /V L] â [â0.17, 0.23] with a correlation of 0.11. The results are in good agreement with the predictions of the Standard Model
Modelling Z â ÏÏ processes in ATLAS with Ï-embedded Z â ΌΌ data
This paper describes the concept, technical realisation and validation of a largely data-driven method to model events with ZâÏÏ decays. In ZâΌΌ events selected from proton-proton collision data recorded at âs=8 TeV with the ATLAS experiment at the LHC in 2012, the Z decay muons are replaced by Ï leptons from simulated ZâÏÏ decays at the level of reconstructed tracks and calorimeter cells. The Ï lepton kinematics are derived from the kinematics of the original muons. Thus, only the well-understood decays of the Z boson and Ï leptons as well as the detector response to the Ï decay products are obtained from simulation. All other aspects of the event, such as the Z boson and jet kinematics as well as effects from multiple interactions, are given by the actual data. This so-called Ï-embedding method is particularly relevant for Higgs boson searches and analyses in ÏÏ final states, where ZarrowÏÏ decays constitute a large irreducible background that cannot be obtained directly from data control samples. In this paper, the relevant concepts are discussed based on the implementation used in the ATLAS Standard Model HâÏÏ analysis of the full datataset recorded during 2011 and 2012
- âŠ