Effects of D-amino acid oxidase inhibition on memory performance and long-term potentiation in vivo

N-methyl-d-aspartate receptor (NMDAR) activation can initiate changes in synaptic strength, evident as long-term potentiation (LTP), and is a key molecular correlate of memory formation. Inhibition of d-amino acid oxidase (DAAO) may increase NMDAR activity by regulating d-serine concentrations, but which neuronal and behavioral effects are influenced by DAAO inhibition remain elusive. In anesthetized rats, extracellular field excitatory postsynaptic potentials (fEPSPs) were recorded before and after a theta frequency burst stimulation (TBS) of the Schaffer collateral pathway of the CA1 region in the hippocampus. Memory performance was assessed after training with tests of contextual fear conditioning (FC, mice) and novel object recognition (NOR, rats). Oral administration of 3, 10, and 30 mg/kg 4H-furo[3,2-b]pyrrole-5-carboxylic acid (SUN) produced dose-related and steady increases of cerebellum d-serine in rats and mice, indicative of lasting inhibition of central DAAO. SUN administered 2 h prior to training improved contextual fear conditioning in mice and novel object recognition memory in rats when tested 24 h after training. In anesthetized rats, LTP was established proportional to the number of TBS trains. d-cycloserine (DCS) was used to identify a submaximal level of LTP (5× TBS) that responded to NMDA receptor activation; SUN administered at 10 mg/kg 3–4 h prior to testing similarly increased in vivo LTP levels compared to vehicle control animals. Interestingly, in vivo administration of DCS also increased brain d-serine concentrations. These results indicate that DAAO inhibition increased NMDAR-related synaptic plasticity during phases of post training memory consolidation to improve memory performance in hippocampal-dependent behavioral tests

Temporal Variability of Diapycnal Mixing in Shag Rocks Passage

Diapycnal mixing rates in the oceans have been shown to have a great deal of spatial variability, but the temporal variability has been little studied. Here we present results from a method developed to calculate diapycnal diffusivity from moored Acoustic Doppler Current Profiler (ADCP) velocity shear profiles. An 18-month time series of diffusivity is presented from data taken by a LongRanger ADCP moored at 2400 m depth, 600 m above the sea floor, in Shag Rocks Passage, a deep passage in the North Scotia Ridge (Southern Ocean). The Polar Front is constrained to pass through this passage, and the strong currents and complex topography are expected to result in enhanced mixing. The spatial distribution of diffusivity in Shag Rocks Passage deduced from lowered ADCP shear is consistent with published values for similar regions, with diffusivity possibly as large as 90 × 10-4 m2 s-1 near the sea floor, decreasing to the expected background level of ~ 0.1 × 10-4 m2 s-1 in areas away from topography. The moored ADCP profiles spanned a depth range of 2400 to 1800 m; thus the moored time series was obtained from a region of moderately enhanced diffusivity. The diffusivity time series has a median of 3.3 × 10-4 m2 s-1 and a range of 0.5 × 10-4 m2 s-1 to 57 × 10-4 m2 s-1. There is no significant signal at annual or semiannual periods, but there is evidence of signals at periods of approximately fourteen days (likely due to the spring-neaps tidal cycle), and at periods of 3.8 and 2.6 days most likely due to topographically-trapped waves propagating around the local seamount. Using the observed stratification and an axisymmetric seamount, of similar dimensions to the one west of the mooring, in a model of baroclinic topographically-trapped waves, produces periods of 3.8 and 2.6 days, in agreement with the signals observed. The diffusivity is anti-correlated with the rotary coefficient (indicating that stronger mixing occurs during times of upward energy propagation), which suggests that mixing occurs due to the breaking of internal waves generated at topography

Climate Process Team on internal wave–driven ocean mixing

Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 98 (2017): 2429-2454, doi:10.1175/BAMS-D-16-0030.1.Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.We are grateful to U.S. CLIVAR for their leadership in instigating and facilitating the Climate Process Team program. We are indebted to NSF and NOAA for sponsoring the CPT series.2018-06-0

Non-linear temperature response of Bragg gratings in doped and un-doped holey polymer optical fibre

We present measurements on the non-linear temperature response of fibre Bragg gratings recorded in pure and trans-4-stilbenemethanol-doped polymethyl methacrylate (PMMA) holey fibres

North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states

Simulation characteristics from eighteen global ocean–sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort

Climate Process Team on Internal-Wave Driven Ocean Mixing

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean, and consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Climate models have been shown to be very sensitive not only to the overall level but to the detailed distribution of mixing; sub-grid-scale parameterizations based on accurate physical processes will allow model forecasts to evolve with a changing climate. Spatio-temporal patterns of mixing are largely driven by the geography of generation, propagation and destruction of internal waves, which are thought to supply much of the power for turbulent mixing. Over the last five years and under the auspices of US CLIVAR, a NSF and NOAA supported Climate Process Team has been engaged in developing, implementing and testing dynamics-base parameterizations for internal-wave driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here we review recent progress, describe the tools developed, and discuss future directions

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

A "target class" screen to identify activators of two-pore domain potassium (K2P) channels

Two-pore domain potassium (K2P) channels carry background (or leak) potassium current and play a key role in regulating resting membrane potential and cellular excitability. Accumulating evidence points to a role for K2Ps in human pathophysiologies, most notably in pain and migraine, making them attractive targets for therapeutic intervention. However, there remains a lack of selective pharmacological tools. The aim of this work was to apply a "target class" approach to investigate the K2P superfamily and identify novel activators across all the described subclasses of K2P channels. Target class drug discovery allows for the leveraging of accumulated knowledge and maximizing synergies across a family of targets and serves as an additional approach to standard target-based screening. A common assay platform using baculovirus (BacMam) to transiently express K2P channels in mammalian cells and a thallium flux assay to determine channel activity was developed, allowing the simultaneous screening of multiple targets. Importantly, this system, by allowing precise titration of channel function, allows optimization to facilitate the identification of activators. A representative set of channels (THIK-1, TWIK-1, TREK-2, TASK-3, and TASK-2) were screened against a library of Food and Drug Administration (FDA)-approved compounds and the LifeArc Index Set. Activators were then analyzed in concentration-response format across all channels to assess selectivity. Using the target class approach to investigate the K2P channels has enabled us to determine which of the K2Ps are amenable to small-molecule activation, de-risk multiple channels from a technical point of view, and identify a diverse range of previously undescribed pharmacology

Potential use of APSIS-InSAR measures of the range of vertical surface motion to improve hazard assessment of peat landslides

Peat landslides represent a notable natural hazard that is difficult to assess across complex blanket bog terrain. To aid the assessment of peat landslide susceptibility, we propose a new metric, the range of vertical surface motion (RVSM), quantified from time series data of surface motion measured using interferometric synthetic aperture radar (InSAR). Our expectation is that areas that are more susceptible to landslide will display a high RVSM that is indicative of high amplitude swelling and shrinking of the peat in response to changes in the volume of water stored in the peat over time. To test our hypothesis we examined the spatial distribution of high RVSM values that preceded three peat landslides in Ireland in 2020 and over a large area of blanket bog. We observed that high RVSM was closely associated with the known failures and with inferred points of initial failure, and that the areas of high RVSM were detectable up to two years in advance of failure. In the blanket bog landscape, high RVSM was associated with areas where landscape hydrology would favour thick peat and subsequent potential instability. We conclude that RVSM mapping has potential for refining national-scale assessments of peat landslide susceptibility