Cardiogenol C can induce Mouse Hair Bulge Progenitor Cells to Transdifferentiate into Cardiomyocyte-like Cells

<p>Abstract</p> <p>Background</p> <p>Hair bulge progenitor cells (HBPCs) are multipotent stem cells derived from the bulge region of mice vibrissal hairs. The purified HBPCs express CD34, K15 and K14 surface markers. It has been reported that HBPCs could be readily induced to transdifferentiate into adipocytes and osteocytes. However, the ability of HBPCs to transdifferentiate into cardiomyocytes has not yet been investigated.</p> <p>Methodology/Principal Findings</p> <p>The cardiomyogenic potential of HBPCs was investigated using a small cell-permeable molecule called Cardiogenol C. We established that Cardiogenol C could induce HBPCs to express transcription factors GATA4, Nkx2.5 and Tbx5, which are early specific markers for pre-cardiomyogenic cells. In prolonged cultures, the Cardiogenol C-treated HBPCs can also express muscle proteins, cardiac-specific troponin I and sarcomeric myosin heavy chain. However, we did not observe the ability of these cells to functionally contract. Hence, we called these cells cardiomyocyte-like cells rather than cardiomyocytes. We tried to remedy this deficiency by pre-treating HBPCs with Valproic acid first before exposing them to Cardiogenol C. This pretreatment inhibited, rather than improved, the effectiveness of Cardiogenol C in reprogramming the HBPCs. We used comparative proteomics to determine how Cardiogenol C worked by identifying proteins that were differentially expressed. We identified proteins that were involved in promoting cell differentiation, cardiomyocyte development and for the normal function of striated muscles. From those differentially expressed proteins, we further propose that Cardiogenol C might exert its effect by activating the Wnt signaling pathway through the suppression of Kremen1. In addition, by up-regulating the expression of chromatin remodeling proteins, SIK1 and Smarce1 would initiate cardiac differentiation.</p> <p>Conclusions/Significance</p> <p>In conclusion, our CD34⁺/K15⁺HBPCs could be induced to transdifferentiate into cardiomyocyte-like cells using a small molecule called Cardiogenol C. The process involves activation of the Wnt signaling pathway and altered expression of several key chromatin remodeling proteins. The finding is clinically significant as HBPCs offer a readily accessible and autologous source of progenitor cells for cell-based therapy of heart disease, which is one of major killers in developed countries.</p

Spontaneous Reaction Silencing in Metabolic Optimization

Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical non-optimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.Comment: 34 pages, 6 figure

Evaluation of diversity among common beans (Phaseolus vulgaris L.) from two centers of domestication using 'omics' technologies

<p>Abstract</p> <p>Background</p> <p>Genetic diversity among wild accessions and cultivars of common bean (<it>Phaseolus vulgaris </it>L.) has been characterized using plant morphology, seed protein allozymes, random amplified polymorphic DNA, restriction fragment length polymorphisms, DNA sequence analysis, chloroplast DNA, and microsatellite markers. Yet, little is known about whether these traits, which distinguish among genetically distinct types of common bean, can be evaluated using omics technologies.</p> <p>Results</p> <p>Three 'omics' approaches: transcriptomics, proteomics, and metabolomics were used to qualitatively evaluate the diversity of common bean from two Centers of Domestication (COD). All three approaches were able to classify common bean according to their COD using unsupervised analyses; these findings are consistent with the hypothesis that differences exist in gene transcription, protein expression, and synthesis and metabolism of small molecules among common bean cultivars representative of different COD. Metabolomic analyses of multiple cultivars within two common bean gene pools revealed cultivar differences in small molecules that were of sufficient magnitude to allow identification of unique cultivar fingerprints.</p> <p>Conclusions</p> <p>Given the high-throughput and low cost of each of these 'omics' platforms, significant opportunities exist for their use in the rapid identification of traits of agronomic and nutritional importance as well as to characterize genetic diversity.</p

Large-Scale Bi-Level Strain Design Approaches and Mixed-Integer Programming Solution Techniques

The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering

STAT5 Is an Ambivalent Regulator of Neutrophil Homeostasis

BACKGROUND: Although STAT5 promotes survival of hematopoietic progenitors, STAT5-/- mice develop mild neutrophilia. METHODOLOGY/PRINCIPAL FINDINGS: Here, we show that in STAT5-/- mice, liver endothelial cells (LECs) autonomously secrete high amounts of G-CSF, allowing myeloid progenitors to overcompensate for their intrinsic survival defect. However, when injected with pro-inflammatory cytokines, mutant mice cannot further increase neutrophil production, display a severe deficiency in peripheral neutrophil survival, and are therefore unable to maintain neutrophil homeostasis. In wild-type mice, inflammatory stimulation induces rapid STAT5 degradation in LECs, G-CSF production by LECs and other cell types, and then sustained mobilization and expansion of long-lived neutrophils. CONCLUSION: We conclude that STAT5 is an ambivalent factor. In cells of the granulocytic lineage, it exerts an antiapoptotic function that is required for maintenance of neutrophil homeostasis, especially during the inflammatory response. In LECs, STAT5 negatively regulates granulopoiesis by directly or indirectly repressing G-CSF expression. Removal of this STAT5-imposed brake contributes to induction of emergency granulopoiesis.Journal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Internet addiction and its psychosocial risks (depression, anxiety, stress and loneliness) among Iranian adolescents and young adults: a structural equation model in a cross-sectional study

Internet addiction has become an increasingly researched area in many Westernized countries. However, there has been little research in developing countries such as Iran, and when research has been conducted, it has typically utilized small samples. This study investigated the relationship of Internet addiction with stress, depression, anxiety, and loneliness in 1,052 Iranian adolescents and young adults. The participants were randomly selected to complete a battery of psychometrically validated instruments including the Internet Addiction Test, Depression Anxiety Stress Scale, and the Loneliness Scale. Structural equation modeling and Pearson correlation coefficients were used to determine the relationship between Internet addiction and psychological impairments (depression, anxiety, stress and loneliness). Pearson correlation, path analysis, multivariate analysis of variance (MANOVA), and t-tests were used to analyze the data. Results showed that Internet addiction is a predictor of stress, depression, anxiety, and loneliness. Findings further indicated that addictive Internet use is gender sensitive and that the risk of Internet addiction is higher in males than in females. The results showed that male Internet addicts differed significantly from females in terms of depression, anxiety, stress, and loneliness. The implications of these results are discussed

A randomized controlled trial of an online, compassion-based intervention for maternal psychological well-being in the first year postpartum

Objectives New self-help interventions have been called for to promote psychological well-being amongst mothers in the first year postpartum, with compassion-based interventions having potential in this regard. The present study developed and evaluated a low-intensity, online, compassion-based intervention for this population called Kindness for Mums Online (KFMO). Methods UK mothers of infants under one year (N = 206) participated in a pragmatic randomized controlled trial, comparing KFMO with a waitlist control. Results The effect of the intervention on well-being (the primary outcome) was small and was sensitive to the way missing data were treated. However, KFMO robustly increased self-compassion relative to control, from baseline (week 0) to post-intervention (week 6), and from baseline to follow-up (week 12). No effects were observed on other secondary outcomes. Conclusions The findings suggest that self-compassion can be increased in postpartum mothers via an accessible, low-intensity, web-based, self-help program. However, this did not translate into robust improvements in well-being. Study limitations include relatively high attrition rates and limited generalizability to more diverse samples

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio