988 resultados para unit delivery model


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Background. Retail clinics, also called convenience care clinics, have become a rapidly growing trend since their initial development in 2000. These clinics are coupled within a larger retail operation and are generally located in "big-box" discount stores such as Wal-mart or Target, grocery stores such as Publix or H-E-B, or in retail pharmacies such as CVS or Walgreen's (Deloitte Center for Health Solutions, 2008). Care is typically provided by nurse practitioners. Research indicates that this new health care delivery system reduces cost, raises quality, and provides a means of access to the uninsured population (e.g., Deloitte Center for Health Solutions, 2008; Convenient Care Association, 2008a, 2008b, 2008c; Hansen-Turton, Miller, Nash, Ryan, Counts, 2007; Salinsky, 2009; Scott, 2006; Ahmed & Fincham, 2010). Some healthcare analysts even suggest that retail clinics offer a feasible solution to the shortage of primary care physicians facing the nation (AHRQ Health Care Innovations Exchange, 2010). ^ The development and performance of retail clinics is heavily dependent upon individual state policies regulating NPs. Texas currently has one of the most highly regulated practice environments for NPs (Stout & Elton, 2007; Hammonds, 2008). In September 2009, Texas passed Senate Bill 532 addressing the scope of practice of nurse practitioners in the convenience care model. In comparison to other states, this law still heavily regulates nurse practitioners. However, little research has been conducted to evaluate the impact of state laws regulating nurse practitioners on the development and performance of retail clinics. ^ Objectives. (1). To describe the potential impact that SB 532 has on retail clinic performance. (2). To discuss the effectiveness, efficiency, and equity of the convenience care model. (3). To describe possible alternatives to Texas' nurse practitioner scope of practice guidelines as delineated in Texas Senate Bill 532. (4). To describe the type of nurse practitioner state regulation (i.e. independent, light, moderate, or heavy) that best promotes the convenience care model. ^ Methods. State regulations governing nurse practitioners can be characterized as independent, light, moderate, and heavy. Four state NP regulatory types and retail clinic performance were compared and contrasted to that of Texas regulations using Dunn and Aday's theoretical models for conducting policy analysis and evaluating healthcare systems. Criteria for measurement included effectiveness, efficiency, and equity. Comparison states were Arizona (Independent), Minnesota (Light), Massachusetts (Moderate), and Florida (Heavy). ^ Results. A comparative states analysis of Texas SB 532 and alternative NP scope of practice guidelines among the four states: Arizona, Florida, Massachusetts, and Minnesota, indicated that SB 532 has minimal potential to affect the shortage of primary care providers in the state. Although SB 532 may increase the number of NPs a physician may supervise, NPs are still heavily restricted in their scope of practice and limited in their ability to act as primary care providers. Arizona's example of independent NP practice provided the best alternative to affect the shortage of PCPs in Texas as evidenced by a lower uninsured rate and less ED visits per 1,000 population. A survey of comparison states suggests that retail clinics thrive in states that more heavily restrict NP scope of practice as opposed to those that are more permissive, with the exception of Arizona. An analysis of effectiveness, efficiency, and equity of the convenience care model indicates that retail clinics perform well in the areas of effectiveness and efficiency; but, fall short in the area of equity. ^ Conclusion. Texas Senate 532 represents an incremental step towards addressing the problem of a shortage of PCPs in the state. A comparative policy analysis of the other four states with varying degrees of NP scope of practice indicate that a more aggressive policy allowing for independent NP practice will be needed to achieve positive changes in health outcomes. Retail clinics pose a temporary solution to the shortage of PCPs and will need to expand their locations to poorer regions and incorporate some chronic care to obtain measurable health outcomes. ^

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Sepsis is a significant cause for multiple organ failure and death in the burn patient, yet identification in this population is confounded by chronic hypermetabolism and impaired immune function. The purpose of this study was twofold: 1) determine the ability of the systemic inflammatory response syndrome (SIRS) and American Burn Association (ABA) criteria to predict sepsis in the burn patient; and 2) develop a model representing the best combination of clinical predictors associated with sepsis in the same population. A retrospective, case-controlled, within-patient comparison of burn patients admitted to a single intensive care unit (ICU) was conducted for the period January 2005 to September 2010. Blood culture results were paired with clinical condition: "positive-sick"; "negative-sick", and "screening-not sick". Data were collected for the 72 hours prior to each blood culture. The most significant predictors were evaluated using logistic regression, Generalized Estimating Equations (GEE) and ROC area under the curve (AUC) analyses to assess model predictive ability. Bootstrapping methods were employed to evaluate potential model over-fitting. Fifty-nine subjects were included, representing 177 culture periods. SIRS criteria were not found to be associated with culture type, with an average of 98% of subjects meeting criteria in the 3 days prior. ABA sepsis criteria were significantly different among culture type only on the day prior (p = 0.004). The variables identified for the model included: heart rate>130 beats/min, mean blood pressure<60 mmHg, base deficit<-6 mEq/L, temperature>36°C, use of vasoactive medications, and glucose>150 mg/d1. The model was significant in predicting "positive culture-sick" and sepsis state, with AUC of 0.775 (p < 0.001) and 0.714 (p < .001), respectively; comparatively, the ABA criteria AUC was 0.619 (p = 0.028) and 0.597 (p = .035), respectively. SIRS criteria are not appropriate for identifying sepsis in the burn population. The ABA criteria perform better, but only for the day prior to positive blood culture results. The time period useful to diagnose sepsis using clinical criteria may be limited to 24 hours. A combination of predictors is superior to individual variable trends, yet algorithms or computer support will be necessary for the clinician to find such models useful. ^

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Allergen-induced asthma is the leading form of asthma and a chronic condition worldwide. Common allergens are known to contribute to the pathogenesis of this disease. Murine models of allergic asthma have mostly used an intraperitoneal route of sensitization (not airway) to study this disease. Allergic asthma pathophysiology involves the activation of TH2-specific cells, which triggers production of IgE antibodies, the up-regulation of TH2-specific cytokines (i.e. IL-4, IL-5, IL-9 and IL-13), increased airway eosinophilia, and mucin hypersecretion. Although there are several therapeutics currently treating asthmatic patients, some of these treatments can result in drug tolerance and may be linked to increased mortality. CpG oligodeoxynucleotides (ODNs) is a synthetic ligand that targets Toll-like Receptor (TLR) 9. It has been evaluated as a therapeutic agent for the treatment of cancer, infectious diseases, and for treating allergy and asthma. PUL-042 is also a synthetic TLR ligand and is composed of two agonists against TLR2/6 heterodimer and TLR9. Previous studies have evaluated PUL-042 for its ability to confer resistance against bacterial and viral lung infection. These findings, combined with studies performed using CpG ODNs, led to speculation that PUL-042 dampens the immune response in allergen-induced asthma. My thesis research investigated airway route sensitization and airway delivery of PUL-042 to evaluate its effects in reducing an allergen-induced asthma phenotype in a murine model. The results of this study contribute to the foundation for future investigations to evaluate the efficacy of PUL-042 as a novel therapy in allergic-asthma disease.

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The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

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Use of Echogenic Immunoliposomes for Delivery of both Drug and Stem Cells for Inhibition of Atheroma Progression By Ali K. Naji B.S. Advisor: Dr. Melvin E. Klegerman PhD Background and significance: Echogenic liposomes can be used as drug and cell delivery vehicles that reduce atheroma progression. Vascular endothelial growth factor (VEGF) is a signal protein that induces vasculogenesis and angiogenesis. VEGF functionally induces migration and proliferation of endothelial cells and increases intracellular vascular permeability. VEGF activates angiogenic transduction factors through VEGF tyrosine kinase domains in high-affinity receptors of endothelial cells. Bevacizumab is a humanized monoclonal antibody specific for VEGF-A which was developed as an anti-tumor agent. Often, anti-VEGF agents result in regression of existing microvessels, inhibiting tumor growth and possibly causing tumor shrinkage with time. During atheroma progression neovasculation in the arterial adventitia is mediated by VEGF. Therefore, bevacizumab may be effective in inhibiting atheroma progression. Stem cells show an ability to inhibit atheroma progression. We have previously demonstrated that monocyte derived CD-34+ stem cells that can be delivered to atheroma by bifunctional-ELIP ( BF-ELIP) targeted to Intercellular Adhesion Molecule-1 (ICAM-1) and CD-34. Adhesion molecules such as ICAM-1 and vascular cell adhesion molecule-1 (VCAM-1) are expressed by endothelial cells under inflammatory conditions. Ultrasound enhanced liposomal targeting provides a method for stem cell delivery into atheroma and encapsulated drug release. This project is designed to examine the ability of echogenic liposomes to deliver bevacizumab and stem cells to inhibit atheroma progression and neovasculation with and without ultrasound in vitro and optimize the ultrasound parameters for delivery of bevacizumab and stem cells to atheroma. V Hypotheses: Previous studies showed that endothelial cell VEGF expression may relate to atherosclerosis progression and atheroma formation in the cardiovascular system. Bevacizumab-loaded ELIP will inhibit endothelial cell VEGF expression in vitro. Bevacizumab activity can be enhanced by pulsed Doppler ultrasound treatment of BEV-ELIP. I will also test the hypothesis that the transwell culture system can serve as an in vitro model for study of US-enhanced targeted delivery of stem cells to atheroma. Monocyte preparations will serve as a source of CD34+ stem cells. Specific Aims: Induce VEGF expression using PKA and PKC activation factors to endothelial cell cultures and use western blot and ELISA techniques to detect the expressed VEGF.  Characterize the relationship between endothelial cell proliferation and VEGF expression to develop a specific EC culture based system to demonstrate BEV-ELIP activity as an anti-VEGF agent. Design a cell-based assay for in vitro assessment of ultrasound-enhanced bevacizumab release from echogenic liposomes.  Demonstrate ultrasound delivery enhancement of stem cells by applying different types of liposomes on transwell EC culture using fluorescently labeled monocytes and detect the effect on migration and attachment rate of these echogenic liposomes with and without ultrasound in vitro.

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Sediment samples from ODP Site 1085 were investigated in order to obtain more information on the initiation and development of the Benguela upwelling system during the middle and upper Miocene. In particular, our intent was to establish the causes of the upwelling as well as the response of the upwelling regime to the development of the Antarctic Circumpolar Current. Based on changes in the calcareous dinoflagellate cyst association, we found an initial increase of the dinoflagellate cyst productivity, probably related to the initiation of upwelling about 11.8 Ma ago. Two distinct increases in cyst productivity in conjunction with temperature decreases of the upper water masses reflect upwelling pulses off Namibia and occur at the end of the Miocene cooling events Mi5 (about 11.5 Ma) and Mi6 (about 10.5 Ma). Both cooling events are associated with an ice volume increase in Antarctica and are thought to have led to an increase in southeasterly winds, possibly causing these two upwelling pulses. We demonstrate a decrease in dinoflagellate cyst productivity and enhanced terrigenous input via the Orange River after the Mi5 event. At about 11.1 Ma, the dinoflagellate cyst productivity increases again. The polar cyst species Caracomia arctica occurs here for the first time. This implies an influence of subantarctic mode water and therefore a change in the quality of the upwelling water which allowed the Benguela upwelling to develop into modern conditions. From about 10.4 Ma, C. arctica forms a permanent part of the association, pointing to an establishment of the upwelling regime.

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This paper assesses the impact of climate change on China's agricultural production at a cross-provincial level using the Ricardian approach, incorporating a multilevel model with farm-level group data. The farm-level group data includes 13379 farm households, across 316 villages, distributed in 31 provinces. The empirical results show that, firstly, the marginal effects and elasticities of net crop revenue per hectare with respect to climate factors indicated that the annual impact of temperature on net crop revenue per hectare was positive, and the effect of increased precipitation was negative when looking at the national totals; secondly, the total impact of simulated climate change scenarios on net crop revenues per hectare at a Chinese national total level, was an increase of between 79 USD per hectare and 207 USD per hectare for the 2050s, and an increase from 140 USD per hectare to 355 USD per hectare for the 2080s. As a result, climate change may create a potential advantage for the development of Chinese agriculture, rather than a risk, especially for agriculture in the provinces of the Northeast, Northwest and North regions. However, the increased precipitation can lead to a loss of net crop revenue per hectare, especially for the provinces of the Southwest, Northwest, North and Northeast regions.

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We are investigating the late Holocene rise in CO2 by performing four experiments with the climate-carbon-cycle model CLIMBER2-LPJ. Apart from the deep sea sediments, important carbon cycle processes considered are carbon uptake or release by the vegetation, carbon uptake by peatlands, and CO 2 release due to shallow water sedimentation of CaCO3. Ice core data of atmospheric CO2 between 8 ka BP and preindustrial climate can only be reproduced if CO2 outgassing due to shallow water sedimentation of CaCO3 is considered. In this case the model displays an increase of nearly 20 ppmv CO2 between 8 ka BP and present day. Model configurations that do not contain this forcing show a slight decrease in atmospheric CO2. We can therefore explain the late Holocene rise in CO2 by invoking natural forcing factors only, and anthropogenic forcing is not required to understand preindustrial CO2 dynamics.

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The paper presents data on the Nd-Sr systematics of magmatic rocks of the Khaidaiskii Series of the Anginskaya Formation in the Ol'khon region, western Baikal area, and rocks of the Talanchanskaya Formation on the eastern shore of Lake Baikal. Geochemical characteristics of these rocks are identical and testify to their arc provenance. At the same time, the epsilon(t)Nd of rocks of the Khaidaiskii Series in the Ol'khon area has positive values, and the data points of these rocks plot near the mantle succession line in the epsilon(t)Nd-87Sr/86Sr diagram, whereas the epsilon(t)Nd values of rocks of the Talanchanskaya Formation are negative, and the data points of these rocks fall into the fourth quadrant in the epsilon(t)Nd -87Sr/86Sr diagram. This testifies to a mantle genesis of the parental magmas of the Khaidaiskii Series and to the significant involvement of older crustal material in the generation of the melts that produced the orthorocks on the eastern shore of the lake. These conclusions are corroborated by model ages of magmatic rocks in the Ol'khon area (close to 1 Ga) and of rocks of the Talanchanskaya Formation (approximately 2 Ga). The comparison of our data with those obtained by other researchers on the Nd-Sr isotopic age of granulites of the Ol'khon Group and metavolcanics in various structural zones in the northern Baikal area suggests, with regard for the geochemistry of these rocks, the accretion of tectonic nappes that had different isotopic histories: some of them were derived from the mantle wedge and localized in the island arc itself (magmatic rocks of the Anginskaya Formation) or backarc spreading zone (mafic metamagmatic rocks of the Ol'khon Group), while others were partial melts derived, with the participation of crustal material, from sources of various age (metagraywackes in the backarc basin in the Ol'khon Group and the ensialic basement of the island arc in the Talanchanskaya Formation).

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Dating of sediment cores from the Baltic Sea has proven to be difficult due to uncertainties surrounding the 14C reservoir age and a scarcity of macrofossils suitable for dating. Here we present the results of multiple dating methods carried out on cores in the Gotland Deep area of the Baltic Sea. Particular emphasis is placed on the Littorina stage (8 ka ago to the present) of the Baltic Sea and possible changes in the 14C reservoir age of our dated samples. Three geochronological methods are used. Firstly, palaeomagnetic secular variations (PSV) are reconstructed, whereby ages are transferred to PSV features through comparison with varved lake sediment based PSV records. Secondly, lead (Pb) content and stable isotope analysis are used to identify past peaks in anthropogenic atmospheric Pb pollution. Lastly, 14C determinations were carried out on benthic foraminifera (Elphidium spec.) samples from the brackish Littorina stage of the Baltic Sea. Determinations carried out on smaller samples (as low as 4 µg C) employed an experimental, state-of-the-art method involving the direct measurement of CO2 from samples by a gas ion source without the need for a graphitisation step - the first time this method has been performed on foraminifera in an applied study. The PSV chronology, based on the uppermost Littorina stage sediments, produced ten age constraints between 6.29 and 1.29 cal ka BP, and the Pb depositional analysis produced two age constraints associated with the Medieval pollution peak. Analysis of PSV data shows that adequate directional data can be derived from both the present Littorina saline phase muds and Baltic Ice Lake stage varved glacial sediments. Ferrimagnetic iron sulphides, most likely authigenic greigite (Fe3S4), present in the intermediate Ancylus Lake freshwater stage sediments acquire a gyroremanent magnetisation during static alternating field (AF) demagnetisation, preventing the identification of a primary natural remanent magnetisation for these sediments. An inferred marine reservoir age offset (deltaR) is calculated by comparing the foraminifera 14C determinations to a PSV & Pb age model. This deltaR is found to trend towards younger values upwards in the core, possibly due to a gradual change in hydrographic conditions brought about by a reduction in marine water exchange from the open sea due to continued isostatic rebound.

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Orbital forcing does not only exert direct insolation effects, but also alters climate indirectly through feedback mechanisms that modify atmosphere and ocean dynamics and meridional heat and moisture transfers. We investigate the regional effects of these changes by detailed analysis of atmosphere and ocean circulation and heat transports in a coupled atmosphere-ocean-sea ice-biosphere general circulation model (ECHAM5/JSBACH/MPI-OM). We perform long term quasi equilibrium simulations under pre-industrial, mid-Holocene (6000 years before present - yBP), and Eemian (125 000 yBP) orbital boundary conditions. Compared to pre-industrial climate, Eemian and Holocene temperatures show generally warmer conditions at higher and cooler conditions at lower latitudes. Changes in sea-ice cover, ocean heat transports, and atmospheric circulation patterns lead to pronounced regional heterogeneity. Over Europe, the warming is most pronounced over the north-eastern part in accordance with recent reconstructions for the Holocene. We attribute this warming to enhanced ocean circulation in the Nordic Seas and enhanced ocean-atmosphere heat flux over the Barents Shelf in conduction with retreat of sea ice and intensified winter storm tracks over northern Europe.

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Although grassland and savanna occupy only a quarter of the world's vegetation, burning in these ecosystems accounts for roughly half the global carbon emissions from fire. However, the processes that govern changes in grassland burning are poorly understood, particularly on time scales beyond satellite records. We analyzed microcharcoal, sediments, and geochemistry in a high-resolution marine sediment core off Namibia to identify the processes that have controlled biomass burning in southern African grassland ecosystems under large, multimillennial-scale climate changes. Six fire cycles occurred during the past 170,000 y in southern Africa that correspond both in timing and magnitude to the precessional forcing of north-south shifts in the Intertropical Convergence Zone. Contrary to the conventional expectation that fire increases with higher temperatures and increased drought, we found that wetter and cooler climates cause increased burning in the study region, owing to a shift in rainfall amount and seasonality (and thus vegetation flammability). We also show that charcoal morphology (i.e., the particle's length-to-width ratio) can be used to reconstruct changes in fire activity as well as biome shifts over time. Our results provide essential context for understanding current and future grassland-fire dynamics and their associated carbon emissions.

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The global aerosol/climate model ECHAM5-HAM is used in order to investigate the dust cycle for four interglacial and one glacial climate conditions. The 20-year time-slices are the pre-industrial control (CTRL), mid-Holocene (6000 years BP), last glacial inception (115000 years BP), Eemian (126000 years BP) and Last Glacial Maximum (LGM) (21000 years BP) time intervals. The study is focused on the Antarctic region. The model is able to reproduce the magnitude order of dust deposition globally for the pre-industial and LGM climates. Correlation coefficient of the natural logarithm of the observed and modeled values is 0.78 for the CTRL and 0.81 for the LGM. For the pre-industrial simulation the model overestimates observed values in Antarctica by a factor of about 2-3 due to overestimation of the Australian dust source and too high wet deposition in the Antarctica interior. In the LGM, the model underestimates dust deposition in eastern Antarctica by a factor of about 4-5 due to underestimation of the South American dust source. More records are needed to validate dust deposition for the past interglacial time-slices. The modeled results show that dust deposition in Antarctica in the past interglacial time-slices is higher than in the CTRL simulation. The largest increase of dust deposition in Antarctica is simulated for the LGM, showing about 10-fold increase compared to CTRL.

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The present dataset contain source data for Figure 5a from Schilling et al., 2009. Cell fate decisions are regulated by the coordinated activation of signalling pathways such as the extracellular signal-regulated kinase (ERK) cascade, but contributions of individual kinase isoforms are mostly unknown. The authors combined quantitative data from erythropoietin-induced pathway activation in primary erythroid progenitor (colony-forming unit erythroid stage, CFU-E) cells with mathematical modelling, in order to predict and experimentally confirmed a distributive ERK phosphorylation mechanism in CFU-E cells. The authors found evidences that double-phosphorylated ERK1 attenuates proliferation beyond a certain activation level, whereas activated ERK2 enhances proliferation with saturation kinetics. Phosphorylation levels of JAK2 at 7 min after stimulation for Epo concentrations ranging from 0.1 to 1000 U/ml were simulated.