Earth is (mostly) flat: Apportionment of the flux of continental sediment over millennial time scales Comment

10.1130/G34846C.1Geology421e316-GLGY

Stabilization of global temperature at 1.5°C and 2.0°C: implications for coastal areas

The effectiveness of stringent climate stabilization scenarios for coastal areas in terms of reduction of impacts/adaptation needs and wider policy implications has received little attention. Here we use the Warming Acidification and Sea Level Projector Earth systems model to calculate large ensembles of global sea-level rise (SLR) and ocean pH projections to 2300 for 1.5°C and 2.0°C stabilization scenarios, and a reference unmitigated RCP8.5 scenario. The potential consequences of these projections are then considered for global coastal flooding, small islands, deltas, coastal cities and coastal ecology. Under both stabilization scenarios, global mean ocean pH (and temperature) stabilize within a century. This implies significant ecosystem impacts are avoided, but detailed quantification is lacking, reflecting scientific uncertainty. By contrast, SLR is only slowed and continues to 2300 (and beyond). Hence, while coastal impacts due to SLR are reduced significantly by climate stabilization, especially after 2100, potential impacts continue to grow for centuries. SLR in 2300 under both stabilization scenarios exceeds unmitigated SLR in 2100. Therefore, adaptation remains essential in densely populated and economically important coastal areas under climate stabilization. Given the multiple adaptation steps that this will require, an adaptation pathways approach has merits for coastal areas. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’

Stochastically Gating Ion Channels Enable Patterned Spike Firing through Activity-Dependent Modulation of Spike Probability

The transformation of synaptic input into patterns of spike output is a fundamental operation that is determined by the particular complement of ion channels that a neuron expresses. Although it is well established that individual ion channel proteins make stochastic transitions between conducting and non-conducting states, most models of synaptic integration are deterministic, and relatively little is known about the functional consequences of interactions between stochastically gating ion channels. Here, we show that a model of stellate neurons from layer II of the medial entorhinal cortex implemented with either stochastic or deterministically gating ion channels can reproduce the resting membrane properties of stellate neurons, but only the stochastic version of the model can fully account for perithreshold membrane potential fluctuations and clustered patterns of spike output that are recorded from stellate neurons during depolarized states. We demonstrate that the stochastic model implements an example of a general mechanism for patterning of neuronal output through activity-dependent changes in the probability of spike firing. Unlike deterministic mechanisms that generate spike patterns through slow changes in the state of model parameters, this general stochastic mechanism does not require retention of information beyond the duration of a single spike and its associated afterhyperpolarization. Instead, clustered patterns of spikes emerge in the stochastic model of stellate neurons as a result of a transient increase in firing probability driven by activation of HCN channels during recovery from the spike afterhyperpolarization. Using this model, we infer conditions in which stochastic ion channel gating may influence firing patterns in vivo and predict consequences of modifications of HCN channel function for in vivo firing patterns

An ALS-Linked Mutant SOD1 Produces a Locomotor Defect Associated with Aggregation and Synaptic Dysfunction When Expressed in Neurons of Caenorhabditis elegans

The nature of toxic effects exerted on neurons by misfolded proteins, occurring in a number of neurodegenerative diseases, is poorly understood. One approach to this problem is to measure effects when such proteins are expressed in heterologous neurons. We report on effects of an ALS-associated, misfolding-prone mutant human SOD1, G85R, when expressed in the neurons of Caenorhabditis elegans. Stable mutant transgenic animals, but not wild-type human SOD1 transgenics, exhibited a strong locomotor defect associated with the presence, specifically in mutant animals, of both soluble oligomers and insoluble aggregates of G85R protein. A whole-genome RNAi screen identified chaperones and other components whose deficiency increased aggregation and further diminished locomotion. The nature of the locomotor defect was investigated. Mutant animals were resistant to paralysis by the cholinesterase inhibitor aldicarb, while exhibiting normal sensitivity to the cholinergic agonist levamisole and normal muscle morphology. When fluorescently labeled presynaptic components were examined in the dorsal nerve cord, decreased numbers of puncta corresponding to neuromuscular junctions were observed in mutant animals and brightness was also diminished. At the EM level, mutant animals exhibited a reduced number of synaptic vesicles. Neurotoxicity in this system thus appears to be mediated by misfolded SOD1 and is exerted on synaptic vesicle biogenesis and/or trafficking

Overexpression of Human and Fly Frataxins in Drosophila Provokes Deleterious Effects at Biochemical, Physiological and Developmental Levels

10 pages, 5 figures. 21779322[PubMed] PMCID: PMC3136927BACKGROUND: Friedreich's ataxia (FA), the most frequent form of inherited ataxias in the Caucasian population, is caused by a reduced expression of frataxin, a highly conserved protein. Model organisms have contributed greatly in the efforts to decipher the function of frataxin; however, the precise function of this protein remains elusive. Overexpression studies are a useful approach to investigate the mechanistic actions of frataxin; however, the existing literature reports contradictory results. To further investigate the effect of frataxin overexpression, we analyzed the consequences of overexpressing human (FXN) and fly (FH) frataxins in Drosophila. METHODOLOGY/PRINCIPAL FINDINGS: We obtained transgenic flies that overexpressed human or fly frataxins in a general pattern and in different tissues using the UAS-GAL4 system. For both frataxins, we observed deleterious effects at the biochemical, histological and behavioral levels. Oxidative stress is a relevant factor in the frataxin overexpression phenotypes. Systemic frataxin overexpression reduces Drosophila viability and impairs the normal embryonic development of muscle and the peripheral nervous system. A reduction in the level of aconitase activity and a decrease in the level of NDUF3 were also observed in the transgenic flies that overexpressed frataxin. Frataxin overexpression in the nervous system reduces life span, impairs locomotor ability and causes brain degeneration. Frataxin aggregation and a misfolding of this protein have been shown not to be the mechanism that is responsible for the phenotypes that have been observed. Nevertheless, the expression of human frataxin rescues the aconitase activity in the fh knockdown mutant. CONCLUSION/SIGNIFICANCE: Our results provide in vivo evidence of a functional equivalence for human and fly frataxins and indicate that the control of frataxin expression is important for treatments that aim to increase frataxin levels.This work was supported by grants from Fondo Investigaciones Sanitarias (ISCIII06- PI0677) and La Fundació la Marató TV3 (exp 101932) of Spain. JVL is supported by the European Friedreich's Ataxia Consortium for Translational Studies. SS is a recipient of a fellowship from Ministerio de Ciencia e Innovación of Spain.Peer reviewe

Integrated modeling in urban hydrology: reviewing the role of monitoring technology in overcoming the issue of ‘big data’ requirements

Increasingly, the application of models in urban hydrology has undergone a shift toward integrated structures that recognize the interconnected nature of the urban landscape and both the natural and engineered water cycles. Improvements in computational processing during the past few decades have enabled the application of multiple, connected model structures that link previously disparate systems together, incorporating feedbacks and connections. Many applications of integrated models look to assess the impacts of environmental change on physical dynamics and quality of landscapes. Whilst these integrated structures provide a more robust representation of natural dynamics, they often place considerable data requirements on the user, whereby data are required at contrasting spatial and temporal scales which can often transcend multiple disciplines. Concomitantly, our ability to observe complex, natural phenomena at contrasting scales has improved considerably with the advent of increasingly novel monitoring technologies. This has provided a pathway for reducing model uncertainty and improving our confidence in modeled outputs by implementing suitable monitoring regimes. This commentary assesses how component models of an exemplar integrated model have advanced over the past few decades, with a critical focus on the role of monitoring technologies that have enabled better identification of the key physical process. This reduces the uncertainty of processes at contrasting spatial and temporal scales, through a better characterization of feedbacks which then enhances the utility of integrated model applications