Metabolic Functions of Peroxisome Proliferator-Activated Receptor β/δ in Skeletal Muscle

Peroxisome proliferator-activated receptors (PPARs) are transcription factors that act as lipid sensors and adapt the metabolic rates of various tissues to the concentration of dietary lipids. PPARs are pharmacological targets for the treatment of metabolic disorders. PPARα and PPARγ are activated by hypolipidemic and insulin-sensitizer compounds, such as fibrates and thiazolidinediones. The roles of PPARβ/δ in metabolic regulations remained unclear until recently. Treatment of obese monkeys and rodents by specific PPARβ/δ agonists promoted normalization of metabolic parameters and reduction of adiposity. Recent evidences strongly suggested that some of these beneficial actions are related to activation of fatty acid catabolism in skeletal muscle and also that PPARβ/δ is involved in the adaptive responses of skeletal muscle to environmental changes, such as long-term fasting or physical exercise, by controlling the number of oxidative myofibers. These observations indicated that PPARβ/δ agonists might have therapeutic usefulness in metabolic syndrome by increasing fatty acid consumption in skeletal muscle and reducing obesity

Peroxisome proliferator-activated receptor β activation promotes myonuclear accretion in skeletal muscle of adult and aged mice

We reported recently that peroxisome proliferator-activated receptor β (PPARβ) activation promotes a calcineurin-dependent exercise-like remodelling characterised by increased numbers of oxidative fibres and capillaries. As physical exercise also induces myonuclear accretion, we investigated whether PPARβ activation alters myonuclear density. Transgenic muscle-specific PPARβ over-expression induced 14% increase of myonuclear density. Pharmacological PPARβ activation promoted rapid and massive myonuclear accretion (20% increase after 48 h), which is dependent upon calcineurin/nuclear factor of activated T cells signalling pathway. In vivo bromodeoxyuridine labelling and proliferating cell nuclear antigen immunodetection revealed that PPARβ activation did not promote cell proliferation, suggesting that the PPARβ-promoted myonuclear accretion involves fusion of pre-existing muscle precursor cells to myofibres rather than cell division. Finally, we showed that in skeletal muscle, ageing led to a down-regulation of PPARβ accompanied by decrease of both oxidative fibre number and myonuclear density. PPARβ pharmacological activation counteracts, at least in part, the ageing-driven muscle remodelling

High binding yet accelerated guest rotation within a cucurbit[7]uril complex. Toward paramagnetic gyroscopes and rolling nanomachines †

International audienceThe (15-oxo-3,7,11-triazadispiro[5.1.5.3]hexadec-7-yl)oxidanyl, a bis-spiropiperidinium nitroxide derived from TEMPONE, can be included in cucurbit[7]uril to form a strong (K a ∼ 2 × 10 5 M −1) CB[7]@bPTO complex. EPR and MS spectra, DFT calculations, and unparalleled increased resistance (a factor of ∼10 3) toward ascorbic acid reduction show evidence of deep inclusion of bPTO inside CB[7]. The unusual shape of the CB[7]@bPTO EPR spectrum can be explained by an anisotropic Brownian rotational diffusion, the global tumbling of the complex being slower than rotation of bPTO around its " long molecular axis " inside CB[7]. The CB[7] (stator) with the encapsulated bPTO (rotator) behaves as a supramolecular para-magnetic rotor with increased rotational speed of the rotator that has great potential for advanced nano-scale machines requiring wheels such as cucurbiturils with virtually no friction between the wheel and the axle for optimum wheel rotation (i.e. nanopulleys and nanocars)

Technical note: Challenges in detecting free tropospheric ozone trends in a sparsely sampled environment

High-quality long-term observational records are essential to ensure appropriate and reliable trend detection of tropospheric ozone. However, the necessity of maintaining high sampling frequency, in addition to continuity, is often under-appreciated. A common assumption is that, so long as long-term records (e.g., a span of a few decades) are available, (1) the estimated trends are accurate and precise, and (2) the impact of small-scale variability (e.g., weather) can be eliminated. In this study, we show that the undercoverage bias (e.g., a type of sampling error resulting from statistical inference based on sparse or insufficient samples, such as once-per-week sampling frequency) can persistently reduce the trend accuracy of free tropospheric ozone, even if multi-decadal time series are considered. We use over 40 years of nighttime ozone observations measured at Mauna Loa, Hawaii (representative of the lower free troposphere), to make this demonstration and quantify the bias in monthly means and trends under different sampling strategies. We also show that short-term meteorological variability remains a cause of an inflated long-term trend uncertainty. To improve the trend precision and accuracy due to sampling bias, two remedies are proposed: (1) a data variability attribution of colocated meteorological influence can efficiently reduce estimation uncertainty and moderately reduce the impact of sparse sampling, and (2) an adaptive sampling strategy based on anomaly detection enables us to greatly reduce the sampling bias and produce more accurate trends using fewer samples compared to an intense regular sampling strategy.</p

Star cluster progenitors are dynamically decoupled from their parent molecular clouds

The formation of stellar clusters dictates the pace at which galaxies evolve, and solving the question of their formation will undoubtedly lead to a better understanding of the Universe as a whole. While it is well known that star clusters form within parsec-scale overdensities of interstellar molecular gas called clumps, it is, however, unclear whether these clumps represent the high-density tip of a continuous gaseous flow that gradually leads towards the formation of stars, or a transition within the gas physical properties. Here, we present a unique analysis of a sample of 27 infrared dark clouds embedded within 24 individual molecular clouds that combine a large set of observations, allowing us to compute the mass and velocity dispersion profiles of each, from the scale of tens of parsecs down to the scale of tenths of a parsec. These profiles reveal that the vast majority of the clouds, if not all, are consistent with being self-gravitating on all scales, and that the clumps, on parsec-scale, are often dynamically decoupled from their surrounding molecular clouds, exhibiting steeper density profiles (ρ∝r−2) and flat velocity dispersion profiles (σ∝r0), clearly departing from Larson’s relations. These findings suggest that the formation of star clusters correspond to a transition regime within the properties of the self-gravitating molecular gas. We propose that this transition regime is one that corresponds to the gravitational collapse of parsec-scale clumps within otherwise stable molecular clouds

Leucine-glycine and carnosine dipeptides prevent diabetes induced by multiple low-dose streptozotocin in experimental model of adult mice

Aims/Introduction Peptides are considered as quasi‐hormones and effective molecules for regulation of the cells function and metabolic disorders prevention. Di‐ and tripeptides with the ability to gastrointestinal absorption have been proposed to prevent diabetes progression. Materials and Methods Small peptides with different sequences of specific amino acids were synthesized based on a solid phase peptide synthesis (SPPS) protocol as well as carnosine (A) and glutathione (B) were examined for the prevention of diabetes induced by multiple low‐dose of streptozotocin (MLDS) in mice. Results The peptides A, Leu‐Gly (D) and Pro‐Pro (F) exhibited a preventive effects on blood glucose elevation and impairment of the signaling and performance of beta cells. The beta cells function assessed by immunofluorescence and blood glucose level in mice exposed to diabetes treated by the peptides A and D was similar to the normal mice. The peptide D prevented from body weight loss caused by diabetes induction. The use of D and A peptides dramatically prevents the incidence of disruption in beta cells signaling by maintaining the natural balance of intracellular Akt‐2 and cAMP. Conclusions The results proved that peptide D (Leu‐Gly) named Hannaneh inhibits the body weight loss caused by diabetes induction. The Hannaneh and carnosine dipeptides with preservation of normal beta cell signalling and anti DPP‐4 activity were prevented from increasing the blood glucose in mice at risk of diabetes. These dipeptides may be regarded as the pharmaceutical agents for the prevention of diabetes

Considering the collision probability of Active Debris Removal missions

Active Debris Removal (ADR) methods are being developed due to a growing concern about the congestion on-orbit and sustainability of spaceflight. This study examined the probability of an on-orbit collision between an ADR target, whilst being de-orbited, and all the objects in the public catalogue published by the US Strategic Command. Such a collision could have significant effects because the target is likely to be located in a densely populated orbital regime and thus follow-on collisions could take place. Six impulsive and three low-thrust example ADR mission trajectories were screened for conjunctions. Extremely close conjunctions were found to result in as much as 99% of the total accumulated collision probability. The need to avoid those conjunctions is highlighted, which raises concerns about ADR methods that do not support collision avoidance. Shortening the removal missions, at an expense of more ?V?V and so cost, will also lower their collision probability by reducing the number of conjunctions that they will experience

Tropospheric Ozone Assessment Report: assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty

Structural Insights into Human Peroxisome Proliferator Activated Receptor Delta (PPAR-Delta) Selective Ligand Binding

Peroxisome proliferator activated receptors (PPARs δ, α and γ) are closely related transcription factors that exert distinct effects on fatty acid and glucose metabolism, cardiac disease, inflammatory response and other processes. Several groups developed PPAR subtype specific modulators to trigger desirable effects of particular PPARs without harmful side effects associated with activation of other subtypes. Presently, however, many compounds that bind to one of the PPARs cross-react with others and rational strategies to obtain highly selective PPAR modulators are far from clear. GW0742 is a synthetic ligand that binds PPARδ more than 300-fold more tightly than PPARα or PPARγ but the structural basis of PPARδ:GW0742 interactions and reasons for strong selectivity are not clear. Here we report the crystal structure of the PPARδ:GW0742 complex. Comparisons of the PPARδ:GW0742 complex with published structures of PPARs in complex with α and γ selective agonists and pan agonists suggests that two residues (Val312 and Ile328) in the buried hormone binding pocket play special roles in PPARδ selective binding and experimental and computational analysis of effects of mutations in these residues confirms this and suggests that bulky substituents that line the PPARα and γ ligand binding pockets as structural barriers for GW0742 binding. This analysis suggests general strategies for selective PPARδ ligand design