Met/HGFR triggers detrimental reactive microglia in TBI

AbstractThe complexity of the signaling events, cellular responses unfolding in neuronal, glial and immune cells upon Traumatic brain injury (TBI) constitutes an obstacle in elucidating pathophysiological links and targets for intervention. We used array phosphoproteomics in a murine mild blunt TBI to reconstruct the temporal dynamics of tyrosine-kinase signaling in TBI and then to scrutinize the large-scale effects of the perturbation of cMet/HGFR, VEGFR1 and Btk signaling by small molecules. cMet/HGFR emerged as a selective modifier of the early microglial response, and cMet/HGFR blockade prevented the induction of microglial inflammatory mediators, of reactive microglia morphology and of TBI-associated responses in neurons, vessels and brain extracellular matrix. Acute or prolonged cMet/HGFR inhibition ameliorated neuronal survival and motor recovery. Early elevation of HGF itself in the CSF of TBI patients suggest that this mechanism has translational value in human subjects. Our findings identify cMet/HGFR as a modulator of early neuroinflammation in TBI with translational potential and indicate several RTK families as possible additional targets for TBI treatment.SummaryControlling neuroinflammation in neurotrauma is an important but unachieved goal. This study exploits a moderate TBI model and array-based proteomics to identify cMet as a new inducer of reactive microglia. A small-molecule inhibitor of cMet contains microglial reactivity, reduces neuronal and vascular alterations, limits behavioural disturbances and accelerates recovery.HighlightsMet is activated in microglia upon TBI and drives microglial reactivity.A Met inhibitor reduces motor dysfunction upon TBI and promotes recovery.Blockade of MET prevents the appearance of a reactive microglia.The cMET inhibitor reduces the sub-acute neuronal loss after TBI.

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Global soil moisture data derived through machine learning trained with in-situ measurements

Scientific Data ◽

10.1038/s41597-021-00964-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Sungmin O. ◽

Rene Orth

Keyword(s):

Machine Learning ◽

Soil Moisture ◽

Large Scale ◽

Short Term Memory ◽

Temporal Dynamics ◽

Soil Moisture Data ◽

Wide Range ◽

Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

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A non-targeted LC–MS metabolic profiling of pregnancy: longitudinal evidence from healthy and pre-eclamptic pregnancies

Metabolomics ◽

10.1007/s11306-020-01752-5 ◽

2021 ◽

Vol 17 (2) ◽

Author(s):

Tiina Jääskeläinen ◽

◽

Olli Kärkkäinen ◽

Jenna Jokkala ◽

Anton Klåvus ◽

...

Keyword(s):

Large Scale ◽

Scale Effects ◽

Late Pregnancy ◽

Metabolite Profile ◽

Adverse Outcomes ◽

Liquid Chromatography Mass Spectrometry ◽

Targeted Metabolomics ◽

Serum Samples ◽

Healthy Women ◽

Maternal Metabolism

Abstract Introduction Maternal metabolism changes substantially during pregnancy. However, few studies have used metabolomics technologies to characterize changes across gestation. Objectives and methods We applied liquid chromatography–mass spectrometry (LC–MS) based non-targeted metabolomics to determine whether the metabolic profile of serum differs throughout the pregnancy between pre-eclamptic and healthy women in the FINNPEC (Finnish Genetics of Preeclampsia Consortium) Study. Serum samples were available from early and late pregnancy. Results Progression of pregnancy had large-scale effects to the serum metabolite profile. Altogether 50 identified metabolites increased and 49 metabolites decreased when samples of early pregnancy were compared to samples of late pregnancy. The metabolic signatures of pregnancy were largely shared in pre-eclamptic and healthy women, only urea, monoacylglyceride 18:1 and glycerophosphocholine were identified to be increased in the pre-eclamptic women when compared to healthy controls. Conclusions Our study highlights the need of large-scale longitudinal metabolomic studies in non-complicated pregnancies before more detailed understanding of metabolism in adverse outcomes could be provided. Our findings are one of the first steps for a broader metabolic understanding of the physiological changes caused by pregnancy per se.

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Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm

Atmosphere ◽

10.3390/atmos12020215 ◽

2021 ◽

Vol 12 (2) ◽

pp. 215

Author(s):

Na Cheng ◽

Shuli Song ◽

Wei Li

Keyword(s):

Magnetic Storm ◽

Large Scale ◽

Temporal Dynamics ◽

Ionospheric Disturbance ◽

Ionospheric Scintillation ◽

Small Scale ◽

Electron Content ◽

Total Electron ◽

Multi Scale ◽

Intense Storm

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.

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Glucose-Limited Fed-Batch Cultivation Strategy to Mimic Large-Scale Effects in Escherichia coli Linked to Accumulation of Non-Canonical Branched-Chain Amino Acids by Combination of Pyruvate Pulses and Dissolved Oxygen Limitation

Microorganisms ◽

10.3390/microorganisms9061110 ◽

2021 ◽

Vol 9 (6) ◽

pp. 1110

Author(s):

Ángel Córcoles García ◽

Peter Hauptmann ◽

Peter Neubauer

Keyword(s):

Amino Acids ◽

Dissolved Oxygen ◽

Large Scale ◽

Scale Effects ◽

Branched Chain Amino Acids ◽

Oxygen Limitation ◽

Fed Batch ◽

Fermentation Products ◽

Cultivation Strategy ◽

Branched Chain

Insufficient mixing in large-scale bioreactors provokes gradient zones of substrate, dissolved oxygen (DO), pH, and other parameters. E. coli responds to a high glucose, low oxygen feeding zone with the accumulation of mixed acid fermentation products, especially formate, but also with the synthesis of non-canonical amino acids, such as norvaline, norleucine and β-methylnorleucine. These amino acids can be mis-incorporated into recombinant products, which causes a problem for pharmaceutical production whose solution is not trivial. While these effects can also be observed in scale down bioreactor systems, these are challenging to operate. Especially the high-throughput screening of clone libraries is not easy, as fed-batch cultivations would need to be controlled via repeated glucose pulses with simultaneous oxygen limitation, as has been demonstrated in well controlled robotic systems. Here we show that not only glucose pulses in combination with oxygen limitation can provoke the synthesis of these non-canonical branched-chain amino acids (ncBCAA), but also that pyruvate pulses produce the same effect. Therefore, we combined the enzyme-based glucose delivery method Enbase® in a PALL24 mini-bioreactor system and combined repeated pyruvate pulses with simultaneous reduction of the aeration rate. These cultivation conditions produced an increase in the non-canonical branched chain amino acids norvaline and norleucine in both the intracellular soluble protein and inclusion body fractions with mini-proinsulin as an example product, and this effect was verified in a 15 L stirred tank bioreactor (STR). To our opinion this cultivation strategy is easy to apply for the screening of strain libraries under standard laboratory conditions if no complex robotic and well controlled parallel cultivation devices are available.

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Modelling Tree Growth in Monospecific Forests from Forest Inventory Data

Forests ◽

10.3390/f12060753 ◽

2021 ◽

Vol 12 (6) ◽

pp. 753

Author(s):

Guadalupe Sáez-Cano ◽

Marcos Marvá ◽

Paloma Ruiz-Benito ◽

Miguel A. Zavala

Keyword(s):

Tree Growth ◽

Large Scale ◽

Temporal Dynamics ◽

Carbon Sink ◽

Size Variation ◽

Biotic Interactions ◽

Richards Equation ◽

Tree Level ◽

Forest Inventories ◽

Large Scale Data

The prediction of tree growth is key to further understand the carbon sink role of forests and the short-term forest capacity on climate change mitigation. In this work, we used large-scale data available from three consecutive forest inventories in a Euro-Mediterranean region and the Bertalanffy–Chapman–Richards equation to model up to a decade’s tree size variation in monospecific forests in the growing stages. We showed that a tree-level fitting with ordinary differential equations can be used to forecast tree diameter growth across time and space as function of environmental characteristics and initial size. This modelling approximation was applied at different aggregation levels to monospecific regions with forest inventories to predict trends in aboveground tree biomass stocks. Furthermore, we showed that this model accurately forecasts tree growth temporal dynamics as a function of size and environmental conditions. Further research to provide longer term prediction forest stock dynamics in a wide variety of forests should model regeneration and mortality processes and biotic interactions.

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Interactions of sapsuckers and Cytospora canker can facilitate decline of riparian willows

Botany ◽

10.1139/cjb-2014-0019 ◽

2014 ◽

Vol 92 (7) ◽

pp. 485-493 ◽

Cited By ~ 3

Author(s):

Kristen M. Kaczynski ◽

David J. Cooper ◽

William R. Jacobi

Keyword(s):

Large Scale ◽

Temporal Dynamics ◽

Rocky Mountain ◽

Aerial Photo ◽

Stream Flows ◽

The Past ◽

Cytospora Chrysosperma ◽

Willow Bark ◽

Moose Population ◽

Cytospora Canker

Drought has caused large-scale plant mortality in ecosystems around the globe. Most diebacks have affected upland forest species. In the past two decades, a large-scale decline of riparian willows (Salix L.) has occurred in Rocky Mountain National Park, Colorado. We examined whether climatic or biotic factors drive and maintain the willow community decline. We compared annual growth and dieback of willows inside and outside of 14-year-old ungulate exclosures and measured groundwater depth and predawn xylem pressures of stems as indicators of drought stress. We also performed an aerial photo analysis to determine the temporal dynamics of the decline. Aerial photo analysis indicated willow decline occurred between 2001 and 2005 and was best explained by an increase in moose population and a decrease in peak stream flows. A new mechanism for willow stem dieback was identified, initiated by red-naped sapsucker wounding willow bark. Wounds became infected with fungus that girdled the stem. DNA analyses confirmed Valsa sordida (Cytospora chrysosperma) as the lethal fungus. Captured sapsuckers had V. sordida spores on feet and beaks identifying them as one possible vector of spread. Predawn xylem pressure potentials remained high through the growing season on all study willows regardless of depth to ground water. Our results indicate that additional mechanisms may be involved in tall willow decline.

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Uncovering the structure and temporal dynamics of information propagation

Network Science ◽

10.1017/nws.2014.3 ◽

2014 ◽

Vol 2 (1) ◽

pp. 26-65 ◽

Cited By ~ 62

Author(s):

MANUEL GOMEZ RODRIGUEZ ◽

JURE LESKOVEC ◽

DAVID BALDUZZI ◽

BERNHARD SCHÖLKOPF

Keyword(s):

News Media ◽

Information Diffusion ◽

Large Scale ◽

Temporal Dynamics ◽

Inference Algorithm ◽

Information Propagation ◽

Transmission Rates ◽

Diffusion Dynamics ◽

Underlying Network ◽

News Events

AbstractTime plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.

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Grabbing Life by the Ballot: Creating an Effective Ballot through Design

Inquiry@Queen's Undergraduate Research Conference Proceedings ◽

10.24908/iqurcp.14022 ◽

2020 ◽

Author(s):

Katharine McCoy

Keyword(s):

Product Design ◽

Design Process ◽

Large Scale ◽

Scale Effects ◽

The World ◽

Ballot Design ◽

The Government ◽

Democratic Elections ◽

Effective Design ◽

Undergraduate Thesis

This presentation, reflecting a politics undergraduate thesis, will explore the design process behind the ballots that voters use in democratic elections around the world. Ballots are an inherently political objects, and in many cases, the most direct line of communication a citizen has to the government of their country. As such, the design of the ballot affects the legitimacy of higher level electoral and democratic institutions. This project argues that by co-opting the language of product design, a universal ballot design process would make more efficient ballots across the globe. Product design starts with a brainstorming stage that explores at the user, the goal of the object, and the context of its use to create an effective design. By applying these observations to the process of designing a ballot, each electoral commission can produce a more effective ballot. Currently there is no standardization for ballot design other than ensuring that electoral commissions tried to make it “friendly.” By examining cases of bad ballot design, it is possible to see what element of the design process was missed or misused to create a process that corrects for these mistakes. This project examines poorly designed ballots in Florida, Scotland, and Colombia to explore the large-scale effects these small design choices make, and how to fix them.

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Overcoming the Challenges of Experimental Research: Lessons From a Criminal Justice Case Study Involving TASER Exposure

Evaluation Review ◽

10.1177/0193841x18803205 ◽

2018 ◽

Vol 42 (3) ◽

pp. 358-385 ◽

Cited By ~ 1

Author(s):

Natalie Todak ◽

Michael D. White ◽

Lisa M. Dario ◽

Andrea R. Borrego

Keyword(s):

Criminal Justice ◽

Large Scale ◽

Human Subjects ◽

Controlled Trial ◽

Human Subjects Research ◽

Case Study Approach ◽

Study Approach ◽

Randomized Controlled ◽

The Impact

Objective: To provide guidance to criminologists for conducting experiments in light of two common discouraging factors: the belief that they are overly time-consuming and the belief that they can compromise the ethical principles of human subjects’ research. Method: A case study approach is used, based on a large-scale randomized controlled trial experiment in which we exposed participants to a 5-s TASER shock, to describe how the authors overcame ethical, methodological, and logistical difficulties. Results: We derive four pieces of advice from our experiences carrying out this experimental trial: (1) know your limitations, (2) employ pilot testing, (3) remain flexible and patient, and (4) “hold the line” to maintain the integrity of the research and the safety of human subjects. Conclusions: Criminologists have an obligation to provide the best possible evidence regarding the impact and consequences of criminal justice practices and programs. Experiments, considered by many to be the gold standard of empirical research methodologies, should be used whenever possible in order to fulfill this obligation.

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Impact of the first COVID-19 shelter-in-place order in the United States on emergency department utilization, Marin County, California

10.1101/2020.07.01.20144691 ◽

2020 ◽

Author(s):

Brett R. Bayles ◽

Michaela F George ◽

Haylea Hannah ◽

Patti Culross ◽

Rochelle R. Ereman ◽

...

Keyword(s):

United States ◽

San Francisco ◽

Large Scale ◽

Temporal Dynamics ◽

The United States ◽

Emergency Department Utilization ◽

Marin County ◽

Before And After ◽

Ed Visits ◽

The Impact

Background: The first shelter-in-place (SIP) order in the United States was issued across six counties in the San Francisco Bay Area to reduce the impact of COVID-19 on critical care resources. We sought to assess the impact of this large-scale intervention on emergency departments (ED) in Marin County, California. Methods: We conducted a retrospective descriptive and trend analysis of all ED visits in Marin County, California from January 1, 2018 to May 4, 2020 to quantify the temporal dynamics of ED utilization before and after the March 17, 2020 SIP order. Results: The average number of ED visits per day decreased by 52.3% following the SIP order compared to corresponding time periods in 2018 and 2019. Both respiratory and non-respiratory visits declined, but this negative trend was most pronounced for non-respiratory admissions. Conclusions: The first SIP order to be issued in the United States in response to COVID-19 was associated with a significant reduction in ED utilization in Marin County.

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