A Theoretical Model for ROP Localisation by Auxin in Arabidopsis Root Hair Cells

Local activation of Rho GTPases is important for many functions including cell polarity, morphology, movement, and growth. Although a number of molecules affecting Rho-of-Plants small GTPase (ROP) signalling are known, it remains unclear how ROP activity becomes spatially organised. Arabidopsis root hair cells produce patches of ROP at consistent and predictable subcellular locations, where root hair growth subsequently occurs.We present a mathematical model to show how interaction of the plant hormone auxin with ROPs could spontaneously lead to localised patches of active ROP via a Turing or Turing-like mechanism. Our results suggest that correct positioning of the ROP patch depends on the cell length, low diffusion of active ROP, a gradient in auxin concentration, and ROP levels. Our theory provides a unique explanation linking the molecular biology to the root hair phenotypes of multiple mutants and transgenic lines, including OX-ROP, CA-rop, aux1, axr3, tip1, eto1, etr1, and the triple mutant aux1 ein2 gnom(eb).We show how interactions between Rho GTPases (in this case ROPs) and regulatory molecules (in this case auxin) could produce characteristic subcellular patterning that subsequently affects cell shape. This has important implications for research on the morphogenesis of plants and other eukaryotes. Our results also illustrate how gradient-regulated Turing systems provide a particularly robust and flexible mechanism for pattern formation

Evaluation of a Command-line Parser-based Order Entry Pathway for the Department of Veterans Affairs Electronic Patient Record

Objective: To improve and simplify electronic order entry in an existing electronic patient record, the authors developed an alternative system for entering orders, which is based on a command- interface using robust and simple natural-language techniques. Design: The authors conducted a randomized evaluation of the new entry pathway, measuring time to complete a standard set of orders, and users' satisfaction measured by questionnaire. A group of 16 physician volunteers from the staff of the Department of Veterans Affairs Puget Sound Health Care System-Seattle Division participated in the evaluation. Results: Thirteen of the 16 physicians (81%) were able to enter medical orders more quickly using the natural-language-based entry system than the standard graphical user interface that uses menus and dialogs (mean time spared, 16.06 ± 4.52 minutes; P=0.029). Compared with the graphical user interface, the command--based pathway was perceived as easier to learn (P<0.01), was considered easier to use and faster (P<0.01), and was rated better overall (P<0.05). Conclusion: Physicians found the command- interface easier to learn and faster to use than the usual menu-driven system. The major advantage of the system is that it combines an intuitive graphical user interface with the power and speed of a natural-language analyze

A comparison of buoy meteorological systems

During May and June 2000, an intercomparison was made of buoy meteorological systems from the Woods Hole Oceanographic Institution (WHOI), the National Oceanographic and Atmospheric Administration (NOAA), Pacific Marine Environmental Laboratory (PMEL), and the Japanese Marine Science and Technology Center (JAMSTEC). Two WHOI systems mounted on a 3 m discus buoy, two PMEL systems mounted on separate buoy tower tops and one JAMSTEC system mounted on a wooden platform were lined parallel to, and 25 m from Nantucket Sound in Massachusetts. All systems used R. M. Young propeller anemometers, Rotronic relative humidity and air temperature sensors and Eppley short-wave radiation sensors. The PMEL and WHOI systems used R. M.Young self-siphoning rain gauges, while the JAMSTEC system used a Scientific Technology ORG-115 optical rain gauge. The PMEL and WHOI systems included an Eppley PIR long-wave sensor, while the JAMSTEC had no longwave sensor. The WHOI system used an AIR DB-1A barometric pressure sensor. PMEL and JAMSTEC systems used Paroscientific Digiquartz sensors. The Geophysical Instruments and Measurements Group (GIM) from Brookhaven National Laboratory (BNL) installed two Portable Radiation Package (PRP) systems that include Eppley short-wave and long-wave sensors on a platform near the site. It was apparent from the data that for most of the sensors, the correlation between data sets was better than the absolute agreement between them. The conclusions made were that the sensors and associated electronics from the three different laboratories performed comparably.Funding was provided by the National Oceanic and Atmospheric Administration under Grant Number NA96GPO429

Testing peatland testate amoeba transfer functions: Appropriate methods for clustered training-sets

Transfer functions are widely used in palaeoecology to infer past environmental conditions from fossil remains of many groups of organisms. In contrast to traditional training-set design with one observation per site, some training-sets, including those for peatland testate amoeba-hydrology transfer functions, have a clustered structure with many observations from each site. Here we show that this clustered design causes standard performance statistics to be overly optimistic. Model performance when applied to independent data sets is considerably weaker than suggested by statistical cross-validation. We discuss the reasons for these problems and describe leave-one-site-out cross-validation and the cluster bootstrap as appropriate methods for clustered training-sets. Using these methods we show that the performance of most testate amoeba-hydrology transfer functions is worse than previously assumed and reconstructions are more uncertain

Expression of an Arc-Immunoreactive Protein in the Adult Zebrafish Brain Increases in Response to a Novel Environment

Zebrafish are a powerful research tool in the field of neuroscience, offering several logistical and physiological advantages over rodents as a research model. However, the molecular dynamics of this model organism, especially with regards to learning and memory, are scarcely known. The current study explored the zebrafish brain for the presence of a protein bearing a similar function to the activity-regulated, cytoskeleton-associated protein (Arc), a critical player in synaptic plasticity. The adult zebrafish brain was found to express a protein with immunoreactivity against the anti-Arc antibody H-300. Immunoreactivity was detected ubiquitously, especially in areas known as adult progenitor cell zones. The protein, termed Arc-immunoreactive protein (AIP), increased in the telencephalon but not the optic tectum 60 min after exposure to a novel environment. Epileptiform brain activity, however, did not induce AIP expression. Evidence presented herein suggests AIP may be the neuropeptide Y receptor rather than a zebrafish homolog of Arc

Shifts and widths of collective excitations in trapped Bose gases by the dielectric formalism

We present predictions for the temperature dependent shifts and damping rates. They are obtained by applying the dielectric formalism to a simple model of a trapped Bose gas. Within the framework of the model we use lowest order perturbation theory to determine the first order correction to the results of Hartree-Fock-Bogoliubov-Popov theory for the complex collective excitation frequencies, and present numerical results for the temperature dependence of the damping rates and the frequency shifts. Good agreement with the experimental values measured at JILA are found for the m=2 mode, while we find disagreements in the shifts for m=0. The latter point to the necessity of a non-perturbative treatment for an explanation of the temperature-dependence of the m=0 shifts.Comment: 10 pages revtex, 3 figures in postscrip

Memory for Semantically Related and Unrelated Declarative Information: The Benefit of Sleep, the Cost of Wake

Numerous studies have examined sleep's influence on a range of hippocampus-dependent declarative memory tasks, from text learning to spatial navigation. In this study, we examined the impact of sleep, wake, and time-of-day influences on the processing of declarative information with strong semantic links (semantically related word pairs) and information requiring the formation of novel associations (unrelated word pairs). Participants encoded a set of related or unrelated word pairs at either 9am or 9pm, and were then tested after an interval of 30 min, 12 hr, or 24 hr. The time of day at which subjects were trained had no effect on training performance or initial memory of either word pair type. At 12 hr retest, memory overall was superior following a night of sleep compared to a day of wakefulness. However, this performance difference was a result of a pronounced deterioration in memory for unrelated word pairs across wake; there was no sleep-wake difference for related word pairs. At 24 hr retest, with all subjects having received both a full night of sleep and a full day of wakefulness, we found that memory was superior when sleep occurred shortly after learning rather than following a full day of wakefulness. Lastly, we present evidence that the rate of deterioration across wakefulness was significantly diminished when a night of sleep preceded the wake period compared to when no sleep preceded wake, suggesting that sleep served to stabilize the memories against the deleterious effects of subsequent wakefulness. Overall, our results demonstrate that 1) the impact of 12 hr of waking interference on memory retention is strongly determined by word-pair type, 2) sleep is most beneficial to memory 24 hr later if it occurs shortly after learning, and 3) sleep does in fact stabilize declarative memories, diminishing the negative impact of subsequent wakefulness

Mental health problems among 4–17-year-olds with hearing problems : results from a nationally representative study

OBJECTIVE : This study aimed to characterize the risk of mental health problems among a representative sample of 6,310 4–17-year-olds, 147 of whom had parent-reported hearing problems. METHODS : The study used data from the Young Minds Matter survey. The Diagnostic Interview Schedule for Children (DISC-IV) assessed prevalence of mood, anxiety and behavioural disorders. The Strengths and Difficulties Questionnaire (SDQ) assessed social and emotional problems. Logistic regression models were used to estimate odds of having mental health problems adjusting for child factors (speech and language problems, global health, age and gender), family factors (family structure, parent income, education, financial strain and psychological distress) and school-related factors (bullying, school liking, school absence). RESULTS : In unadjusted analyses, children and young people with hearing problems had substantially higher odds of most mental health problems. Hearing problems were not associated with any mental health problem among 4–11-year-olds after adjusting for other child factors. After adjustments for child, family and school-related factors, 12–17-year-olds with a hearing problem remained at greater risk of social phobia and generalized anxiety (DISC-IV), and of peer and emotional problems (SDQ). CONCLUSIONS : Clinicians caring for children and young people with hearing problems should be alert for heightened risk of specific mental health problems based on age and the nature of hearing problems. Understanding a wider range of correlates associated with the higher prevalence of mental health problems may allow health professionals to be more informed about the nature of mental health problems that are comorbid to hearing problems.KJH was supported by the Australian Research Centre of Excellence for Children and Families over the Life Course [grant No. CE140100027]. AL was supported by a National Health and Medical Research Council Early Career Fellowship [grant No. 1072593]. The Young Minds Matter survey was initiated and funded by the Australian Government Department of Health.https://www.tandfonline.com/toc/ihbc202018-05-16hj2018Speech-Language Pathology and Audiolog

HopScotch - a low-power renewable energy base station network for rural broadband access

The provision of adequate broadband access to communities in sparsely populated rural areas has in the past been severely restricted. In this paper, we present a wireless broadband access test bed running in the Scottish Highlands and Islands which is based on a relay network of low-power base stations. Base stations are powered by a combination of renewable sources creating a low cost and scalable solution suitable for community ownership. The use of the 5~GHz bands allows the network to offer large data rates and the testing of ultra high frequency ``white space'' bands allow expansive coverage whilst reducing the number of base stations or required transmission power. We argue that the reliance on renewable power and the intelligent use of frequency bands makes this approach an economic green radio technology which can address the problem of rural broadband access

Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° x 5° and up to 50 km x 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a−1, as compared to 24.9-27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20 % to landfills/wastewater, and 11-15 % to coal. Wetlands contribute an additional 9.0-10.1 Tg a−1