Mathematical model of bursting in dissociated Purkinje neurons

In vitro, Purkinje cell behaviour is sometimes studied in a dissociated soma preparation in which the dendritic projection has been cleaved. A fraction of these dissociated somas spontaneously burst. The mechanism of this bursting is incompletely understood. We have constructed a biophysical Purkinje soma model, guided and constrained by experimental reports in the literature, that can replicate the somatically driven bursting pattern and which hypothesises Persistent Na+ current (INaP) to be its burst initiator and SK K+ current (ISK) to be its burst terminator

Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster

Background: An approach to investigate brain function/dysfunction is to simulate neuron circuits on a computer. A problem, however, is that detailed neuron descriptions are computationally expensive and this handicaps the pursuit of realistic network investigations, where many neurons need to be simulated. Results: We confront this issue; we employ a novel reduction algorithm to produce a 2 compartment model of the cerebellar Purkinje neuron from a previously published, 1089 compartment model. It runs more than 400 times faster and retains the electrical behavior of the full model. So, it is more suitable for inclusion in large network models, where computational power is a limiting issue. We show the utility of this reduced model by demonstrating that it can replicate the full model’s response to alcohol, which can in turn reproduce experimental recordings from Purkinje neurons following alcohol application. Conclusions: We show that alcohol may modulate Purkinje neuron firing by an inhibition of their sodium-potassium pumps. We suggest that this action, upon cerebellar Purkinje neurons, is how alcohol ingestion can corrupt motor co-ordination. In this way, we relate events on the molecular scale to the level of behavior

The sodium-potassium pump controls the intrinsic firing of the cerebellar Purkinje neuron

In vitro, cerebellar Purkinje cells can intrinsically fire action potentials in a repeating trimodal or bimodal pattern. The trimodal pattern consists of tonic spiking, bursting, and quiescence. The bimodal pattern consists of tonic spiking and quiescence. It is unclear how these firing patterns are generated and what determines which firing pattern is selected. We have constructed a realistic biophysical Purkinje cell model that can replicate these patterns. In this model, Na+/K+ pump activity sets the Purkinje cell's operating mode. From rat cerebellar slices we present Purkinje whole cell recordings in the presence of ouabain, which irreversibly blocks the Na+/K+ pump. The model can replicate these recordings. We propose that Na+/K+ pump activity controls the intrinsic firing mode of cerbellar Purkinje cells

A direct quantitative measure of surface mobility in a glassy polymer

Thin polymer films have striking dynamical properties that differ from their bulk counterparts. With the simple geometry of a stepped polymer film on a substrate, we probe mobility above and below the glass transition temperature $T_{\textrm{g}}$. Above $T_{\textrm{g}}$ the entire film flows, while below $T_{\textrm{g}}$ only the near surface region responds to the excess interfacial energy. An analytical thin film model for flow limited to the free surface region shows excellent agreement with sub-$T_{\textrm{g}}$ data. The system transitions from whole film flow to surface localized flow over a narrow temperature region near the bulk $T_{\textrm{g}}$. The experiments and model provide a measure of surface mobility in a sample geometry where confinement and substrate effects are negligible. This fine control of the glassy rheology is of key interest to nanolithography among numerous other applications

Wildfire, climate, and perceptions in northeast Oregon

Wildfire poses a rising threat in the western USA, fueled by synergies between historical fire suppression, changing land use, insects and disease, and shifts toward a drier, warmer climate. The rugged landscapes of northeast Oregon, with their historically forest- and resource-based economies, have been one of the areas affected. A 2011 survey found area residents highly concerned about fire and insect threats, but not about climate change. In 2014 we conducted a second survey that, to explore this apparent disconnect, included questions about past and future summertime (fire season) temperatures. Although regional temperatures have warmed in recent decades at twice the global rate, accompanied by increasing dryness and fire risks, the warming itself is recognized by only 40 % of our respondents. Awareness of recent warming proves unrelated to individual characteristics that might indicate experience on the land: old-timer versus newcomer status, year-round versus seasonal residence, and ownership of forested land. Perceptions of past warming and expectations of future warming are more common among younger respondents and less common among Tea Party supporters. The best-educated partisans stand farthest apart. Perceptions about local temperatures that are important for adaptation planning thus follow ideological patterns similar to beliefs about global climate change

Forest Views: Shifting Attitudes Toward the Environment in Northeast Oregon

This brief reports on a telephone survey conducted in fall 2014 as part of the ongoing Communities and Forests in Oregon (CAFOR) project. CAFOR focuses on seven counties in the Blue Mountains of northeast Oregon (Baker, Crook, Grant, Umatilla, Union, Wallowa, and Wheeler), where the landscape and local livelihoods are changing in interconnected ways. In an effort to inform policy development around natural resource management, the study seeks to understand how public perceptions of climate change and forest management intersect. Authors Angela Boag, Joel Hartter, Lawrence Hamilton, Forrest Stevens, Mark Ducey, Michael Palace, Nils Christoffersen, and Paul Oester report that 65 percent of those surveyed believe that forests are less healthy than they were twenty years ago. Approximately half of residents support increased user fees to improve forest health on federal land, and a majority believes that climate change is happening, although opinion is split between those who believe it is human-caused and those who believe it is caused by natural forces. The authors conclude that innovative economic and policy solutions are needed across the Inland West to help people and forests regain a strong and productive relationship that both supports livelihoods and sustains working landscapes

Does it matter if people think climate change is human caused?

There is a growing consensus that climate is changing, but beliefs about the causal factors vary widely among the general public. Current research shows that such causal beliefs are strongly influenced by cultural, political, and identity-driven views. We examined the influence that local perceptions have on the acceptance of basic facts about climate change. We also examined the connection to wildfire by local people. Two recent telephone surveys found that 37% (in 2011) and 46% (in 2014) of eastern Oregon (USA) respondents accept the scientific consensus that human activities are now changing the climate. Although most do not agree with that consensus, large majorities (85–86%) do agree that climate is changing, whether by natural or human causes. Acceptance of anthropogenic climate change generally divides along political party lines, but acceptance of climate change more generally, and concerns about wildfire, transcend political divisions. Support for active forest management to reduce wildfire risks is strong in this region, and restoration treatments could be critical to the resilience of both communities and ecosystems. Although these immediate steps involve adaptations to a changing climate, they can be motivated without necessarily invoking human-caused climate change, a divisive concept among local landowners

Inhibition effect of a custom peptide on lung tumors

Cecropin B is a natural antimicrobial peptide and CB1a is a custom, engineered modification of it. In vitro, CB1a can kill lung cancer cells at concentrations that do not kill normal lung cells. Furthermore, in vitro, CB1a can disrupt cancer cells from adhering together to form tumor-like spheroids. Mice were xenografted with human lung cancer cells; CB1a could significantly inhibit the growth of tumors in this in vivo model. Docetaxel is a drug in present clinical use against lung cancers; it can have serious side effects because its toxicity is not sufficiently limited to cancer cells. In our studies in mice: CB1a is more toxic to cancer cells than docetaxel, but dramatically less toxic to healthy cells

Electromagnetically Induced Transparency with Noisy Lasers

We demonstrate and characterize two coherent phenomena that can mitigate the effects of laser phase noise for Electromagnetically Induced Transparency (EIT): a laser-power-broadening-resistant resonance in the transmitted intensity cross-correlation between EIT optical fields; and a resonant suppression of the conversion of laser phase noise to intensity noise when one-photon noise dominates over two-photon-detuning noise. Our experimental observations are in good agreement with both an intuitive physical picture and numerical calculations. The results have wide-ranging applications to spectroscopy, atomic clocks and magnetometers.Physic

Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et a