84 research outputs found

    Regulation of glutamatergic signalling by PACAP in the mammalian suprachiasmatic nucleus

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    BACKGROUND: Previous studies indicate that light information reaches the suprachiasmatic nucleus (SCN) through a subpopulation of retinal ganglion cells that contain both glutamate and pituitary adenylyl cyclase activating peptide (PACAP). While the role of glutamate in this pathway has been well studied, the involvement of PACAP and its receptors are only beginning to be understood. Speculating that PACAP may function to modulate how neurons in the suprachiasmatic nucleus respond to glutamate, we used electrophysiological and calcium imaging tools to examine possible cellular interactions between these co-transmitters. RESULTS: Exogenous application of PACAP increased both the amplitude and frequency of spontaneous excitatory postsynaptic currents recorded from SCN neurons in a mouse brain slice preparation. PACAP also increased the magnitude of AMPA-evoked currents through a mechanism mediated by PAC1 receptors and the adenylyl cyclase-signalling cascade. This enhancement of excitatory currents was not limited to those evoked by AMPA as the magnitude of NMDA currents were also enhanced by application of PACAP. Furthermore, PACAP enhanced AMPA and NMDA evoked calcium transients while PACAP alone produced very little change in resting calcium in most mouse SCN neurons. Finally, in rat SCN neurons, exogenous PACAP enhanced AMPA evoked currents and calcium transients as well evoked robust calcium transients on its own. CONCLUSION: The results reported here show that PACAP is a potent modulator of glutamatergic signalling within the SCN in the early night

    Microbial activity in the marine deep biosphere: progress and prospects

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    The vast marine deep biosphere consists of microbial habitats within sediment, pore waters, upper basaltic crust and the fluids that circulate throughout it. A wide range of temperature, pressure, pH, and electron donor and acceptor conditions exists—all of which can combine to affect carbon and nutrient cycling and result in gradients on spatial scales ranging from millimeters to kilometers. Diverse and mostly uncharacterized microorganisms live in these habitats, and potentially play a role in mediating global scale biogeochemical processes. Quantifying the rates at which microbial activity in the subsurface occurs is a challenging endeavor, yet developing an understanding of these rates is essential to determine the impact of subsurface life on Earth\u27s global biogeochemical cycles, and for understanding how microorganisms in these “extreme” environments survive (or even thrive). Here, we synthesize recent advances and discoveries pertaining to microbial activity in the marine deep subsurface, and we highlight topics about which there is still little understanding and suggest potential paths forward to address them. This publication is the result of a workshop held in August 2012 by the NSF-funded Center for Dark Energy Biosphere Investigations (C-DEBI) “theme team” on microbial activity (www.darkenergybiosphere.org)

    WMO evaluation of northern hemispheric coldest temperature: −69.6 °C at Klinck, Greenland, 22 December 1991

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    A World Meteorological Organization (WMO) Extremes Evaluation Committee investigated an observation of −69.6 °C by Klinck Automatic Weather Station (AWS) in Greenland on 22 December 1991 as the lowest temperature observed in Greenland, thereby making it the lowest recorded near‐surface air temperature for the Northern and Western Hemispheres and for WMO Region VI. The committee examined the metadata and observations of the station as well as the regional synoptic circulation. The committee concluded that the observation is credible in terms of instrument calibration, monitoring of the station and the synoptic situation. Consequently, the WMO Rapporteur accepted the observation as the officially lowest observed near‐surface air temperature for Greenland, the Northern and Western Hemisphere and for WMO Region VI. As a supplement to this investigation, the committee also recommends that opportunities be investigated such that AWS data from Greenland can be efficiently incorporated into real‐time weather forecasts and hence into reanalysis datasets

    The state of the Martian climate

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    60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

    Correction for Johansson et al., An open challenge to advance probabilistic forecasting for dengue epidemics.

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    Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116. The authors note that the affiliation for Xavier Rodó should instead appear as Catalan Institution for Research and Advanced Studies (ICREA) and Climate and Health Program, Barcelona Institute for Global Health (ISGlobal). The corrected author and affiliation lines appear below. The online version has been corrected

    A communal catalogue reveals Earth's multiscale microbial diversity

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    Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

    A communal catalogue reveals Earth’s multiscale microbial diversity

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    Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

    An open challenge to advance probabilistic forecasting for dengue epidemics.

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    A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue
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