Low redshift constraints on energy-momentum-powered gravity models

There has been recent interest in the cosmological consequences of energy-momentum-powered gravity models, in which the matter side of Einstein's equations is modified by the addition of a term proportional to some power, $n$, of the energy-momentum tensor, in addition to the canonical linear term. In this work we treat these models as phenomenological extensions of the standard $\Lambda$CDM, containing both matter and a cosmological constant. We also quantitatively constrain the additional model parameters using low redshift background cosmology data that are specifically from Type Ia supernovas and Hubble parameter measurements. We start by studying specific cases of these models with fixed values of $n,$ which lead to an analytic expression for the Friedmann equation; we discuss both their current constraints and how the models may be further constrained by future observations of Type Ia supernovas for WFIRST complemented by measurements of the redshift drift by the ELT. We then consider and constrain a more extended parameter space, allowing $n$ to be a free parameter and considering scenarios with and without a cosmological constant. These models do not solve the cosmological constant problem per se. Nonetheless these models can phenomenologically lead to a recent accelerating universe without a cosmological constant at the cost of having a preferred matter density of around $\Omega_M\sim0.4$ instead of the usual $\Omega_M\sim0.3$. Finally we also briefly constrain scenarios without a cosmological constant, where the single component has a constant equation of state which needs not be that of matter; we provide an illustrative comparison of this model with a more standard dynamical dark energy model with a constant equation of state.Comment: 13+2 pages, 12+1 figures; A&A (in press

Does degradation from selective logging and illegal activities differently impact forest resources? A case study in Ghana

Degradation, a reduction of the ecosystem’s capacity to supply goods and services, is widespread in tropical forests and mainly caused by human disturbance. To maintain the full range of forest ecosystem services and support the development of effective conservation policies, we must understand the overall impact of degradation on different forest resources. This research investigates the response to disturbance of forest structure using several indicators: soil carbon content, arboreal richness and biodiversity, functional composition (guild and wood density), and productivity. We drew upon large field and remote sensing datasets from different forest types in Ghana, characterized by varied protection status, to investigate impacts of selective logging, and of illegal land use and resources extraction, which are the main disturbance causes in West Africa. Results indicate that functional composition and the overall number of species are less affected by degradation, while forest structure, soil carbon content and species abundance are seriously impacted, with resources distribution reflecting the protection level of the areas. Remote sensing analysis showed an increase in productivity in the last three decades, with higher resiliency to change in drier forest types, and stronger productivity correlation with solar radiation in the short dry season. The study region is affected by growing anthropogenic pressure on natural resources and by an increased climate variability: possible interactions of disturbance with climate are also discussed, together with the urgency to reduce degradation in order to preserve the full range of ecosystem functions

"The difference that makes a difference": highlighting the role of variable contexts within an HIV Prevention Community Randomised Trial (HPTN 071/PopART) in 21 study communities in Zambia and South Africa.

This paper explores contextual heterogeneity within a community randomised trial HPTN 071 (Population Effects of Antiretroviral Treatment to Reduce HIV Transmission) carried out in 21 study communities (12 Zambian, 9 South African). The trial evaluates the impact of a combination HIV prevention package (including household-based HIV counselling and testing and anti-retroviral treatment (ART) eligibility regardless of CD4-count) on HIV incidence. The selection, matching and randomisation of study communities relied on key epidemiological and demographic variables and community and stakeholder support. In 2013, following the selection of study communities, a "Broad Brush Survey" (BBS) approach was used to rapidly gather qualitative data on each study community, prior to the implementation of the trial intervention. First-year process indicator intervention data (2014-2015) were collected during the household-based intervention by community lay workers. Using an open/closed typology of urban communities (indicating more or less heterogeneity), this qualitative inquiry presents key features of 12 Zambian communities using a list of four meta-indicators (physical features, social organisation, networks and community narratives). These indicators are then compared with four intervention process indicators in a smaller set of four study communities. The process indicators selected for this analysis indicate response to the intervention (uptake) amongst adults. The BBS qualitative data are used to interpret patterns of similarity and variability in the process indicators across four communities. We found that meta-indicators of local context helped to interpret patterns of similarity and variability emerging across and within the four communities. Features especially significant for influencing heterogeneity in process indicators include proportion of middle-class residents, proximity to neighbouring communities and town centre, the scale of the informal economy, livelihood-linked mobility, presence of HIV stakeholders over time and commitment to community action. Future interdisciplinary analysis is needed to explore if these patterns of difference continue to hold up over the full intervention period and all intervention communities

The induction of α-helical structure in partially unfolded HypF-N does not affect its aggregation propensity

The conversion of proteins into structured fibrillar aggregates is a central problem in protein chemistry, biotechnology, biology and medicine. It is generally accepted that aggregation takes place from partially structured states of proteins. However, the role of the residual structure present in such conformational states is not yet understood. In particular, it is not yet clear as to whether the α-helical structure represents a productive or counteracting structural element for protein aggregation. We have addressed this issue by studying the aggregation of pH-unfolded HypF-N. It has previously been shown that the two native α-helices of HypF-N retain a partial α-helical structure in the pH-unfolded state and that these regions are also involved in the formation of the cross-β structure of the aggregates. We have introduced mutations in such stretches of the sequence, with the aim of increasing the α-helical structure in the key regions of the pH-unfolded state, while minimizing the changes of other factors known to influence protein aggregation, such as hydrophobicity, β-Sheet propensity, etc. The resulting HypF-N mutants have higher contents of α-helical structure at the site(s) of mutation in their pH-unfolded states, but such an increase does not correlate with a change of aggregation rate. The results suggest that stabilisation of α-helical structure in amyloidogenic regions of the sequence of highly dynamic states does not have remarkable effects on the rate of protein aggregation from such conformational states. Comparison with other protein systems indicate that the effect of increasing α-helical propensity can vary if the stabilised helices are in non-amyloidogenic stretches of initially unstructured peptides (accelerating effect), in amyloidogenic stretches of initially unstructured peptides (no effect) or in amyloidogenic stretches of initially stable helices (decelerating effect

Interaction of toxic and non-toxic HypF-N oligomers with lipid bilayers investigated at high resolution with atomic force microscopy

Protein misfolded oligomers are considered the most toxic species amongst those formed in the process of amyloid formation and the molecular basis of their toxicity, although not completely understood, is thought to originate from the interaction with the cellular membrane. Here, we sought to highlight the molecular determinants of oligomer-membrane interaction by atomic force microscopy. We monitored the interaction between multiphase supported lipid bilayers and two types of HypF-N oligomers displaying different structural features and cytotoxicities. By our approach we imaged with unprecedented resolution the ordered and disordered lipid phases of the bilayer and different oligomer structures interacting with either phase. We identified the oligomers and lipids responsible for toxicity and, more generally, we established the importance of the membrane lipid component in mediating oligomer toxicity. Our findings support the importance of GM1 ganglioside in mediating the oligomer-bilayer interaction and support a mechanism of oligomer cytotoxicity involving bilayer destabilization by globular oligomers within GM1-rich ordered raft regions rather than by annular oligomers in the surrounding disordered membrane domains

Three-body Interactions Improve the Prediction of Rate and Mechanism in Protein Folding Models

Here we study the effects of many-body interactions on rate and mechanism in protein folding, using the results of molecular dynamics simulations on numerous coarse-grained C-alpha-model single-domain proteins. After adding three-body interactions explicitly as a perturbation to a Go-like Hamiltonian with native pair-wise interactions only, we have found 1) a significantly increased correlation with experimental phi-values and folding rates, 2) a stronger correlation of folding rate with contact order, matching the experimental range in rates when the fraction of three-body energy in the native state is ~ 20%, and 3) a considerably larger amount of 3-body energy present in Chymotripsin inhibitor than other proteins studied.Comment: 9 pages, 2 tables and 5 figure

Systematic In Vivo Analysis of the Intrinsic Determinants of Amyloid β Pathogenicity

Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Aβ42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Aβ42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Aβ and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism

Amyloid fibril length distribution quantified by atomic force microscopy single-particle image analysis

Amyloid fibrils are proteinaceous nano-scale linear aggregates. They are of key interest not only because of their association with numerous disorders, such as type II diabetes mellitus, Alzheimer's and Parkinson's diseases, but also because of their potential to become engineered high-performance nano-materials. Methods to characterise the length distribution of nano-scale linear aggregates such as amyloid fibrils are of paramount importance both in understanding the biological impact of these aggregates and in controlling their mechanical properties as potential nano-materials. Here, we present a new quantitative approach to the determination of the length distribution of amyloid fibrils using tapping-mode atomic force microscopy. The method described employs single-particle image analysis corrected for the length-dependent bias that is a common problem associated with surface-based imaging techniques. Applying this method, we provide a detailed characterisation of the length distribution of samples containing long-straight fibrils formed in vitro from β2-microglobulin. The results suggest that the Weibull distribution is a suitable model in describing fibril length distributions, and reveal that fibril fragmentation is an important process even under unagitated conditions. These results demonstrate the significance of quantitative length distribution measurements in providing important new information regarding amyloid assembly