Fetal programming of adipose tissue function: an evolutionary perspective

Obesity is an escalating threat of pandemic proportions and has risen to such unrivaled prominence in such a short period of time that it has come to define a whole generation in many countries around the globe. The burden of obesity, however, is not equally shared among the population, with certain ethnicities being more prone to obesity than others, while some appear to be resistant to obesity altogether. The reasons behind this ethnic basis for obesity resistance and susceptibility, however, have remained largely elusive. In recent years, much evidence has shown that the level of brown adipose tissue thermogenesis, which augments energy expenditure and is negatively associated with obesity in both rodents and humans, varies greatly between ethnicities. Interestingly, the incidence of low birth weight, which is associated with an increased propensity for obesity and cardiovascular disease in later life, has also been shown to vary by ethnic background. This review serves to reconcile ethnic variations in BAT development and function with ethnic differences in birth weight outcomes to argue that the variation in obesity susceptibility between ethnic groups may have its origins in the in utero programming of BAT development and function as a result of evolutionary adaptation to cold environments.

Generalized convective quasi-equilibrium principle

A generalization of Arakawa and Schubert's convective quasi-equilibrium principle is presented for a closure formulation of mass-flux convection parameterization. The original principle is based on the budget of the cloud work function. This principle is generalized by considering the budget for a vertical integral of an arbitrary convection-related quantity. The closure formulation includes Arakawa and Schubert's quasi-equilibrium, as well as both CAPE and moisture closures as special cases. The formulation also includes new possibilities for considering vertical integrals that are dependent on convective-scale variables, such as the moisture within convection. The generalized convective quasi-equilibrium is defined by a balance between large-scale forcing and convective response for a given vertically-integrated quantity. The latter takes the form of a convolution of a kernel matrix and a mass-flux spectrum, as in the original convective quasi-equilibrium. The kernel reduces to a scalar when either a bulk formulation is adopted, or only large-scale variables are considered within the vertical integral. Various physical implications of the generalized closure are discussed. These include the possibility that precipitation might be considered as a potentially-significant contribution to the large-scale forcing. Two dicta are proposed as guiding physical principles for the specifying a suitable vertically-integrated quantity.

Enzymatically-triggered, isothermally responsive polymers: re-programming poly(oligoethylene glycols) to respond to phosphatase

Polymers which can respond to externally applied stimuli have found much application in the biomedical field due to their (reversible) coil–globule transitions. Polymers displaying a lower critical solution temperature are the most commonly used, but for blood-borne (i.e., soluble) biomedical applications the application of heat is not always possible, nor practical. Here we report the design and synthesis of poly(oligoethylene glycol methacrylate)-based polymers whose cloud points are easily varied by alkaline phosphatase-mediated dephosphorylation. By fine-tuning the density of phosphate groups on the backbone, it was possible to induce an isothermal transition: A change in solubility triggered by removal of a small number of phosphate esters from the side chains activating the LCST-type response. As there was no temperature change involved, this serves as a model of a cell-instructed polymer response. Finally, it was found that both polymers were non cytotoxic against MCF-7 cells (at 1 mg·mL–1), which confirms promise for biomedical applications.

Generalized drivers in the mammalian endangerment process

An important challenge for conservation today is to understand the endangerment process and identify any generalized patterns in how threats occur and aggregate across taxa. Here we use a global database describing main current external threats in mammals to evaluate the prevalence of distinct threatening processes, primarily of anthropogenic origin, and to identify generalized drivers of extinction and their association with vulnerability status and intrinsic species' traits. We detect several primary threat combinations that are generally associated with distinct species. In particular, large and widely distributed mammals are affected by combinations of direct exploitation and threats associated with increasing landscape modification that go from logging to intense human land-use. Meanwhile, small, narrowly distributed species are affected by intensifying levels of landscape modification but are not directly exploited. In general more vulnerable species are affected by a greater number of threats, suggesting increased extinction risk is associated with the accumulation of external threats. Overall, our findings show that endangerment in mammals is strongly associated with increasing habitat loss and degradation caused by human land-use intensification. For large and widely distributed mammals there is the additional risk of being hunted.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Schatten class Toeplitz operators on generalized Fock spaces

In this paper we characterize the Schatten p class membership of Toeplitz operators with positive measure symbols acting on generalized Fock spaces for the full range p>0.