Inflammatory and angiogenic protein detection in the human vitreous : cytometric bead assay

Introduction. To evaluate clinical feasibility and reproducibility of cytometric bead assay (CBA) in nondiluted vitreous samples of patients with age-related macular degeneration (ARMD), diabetic macular edema (DME), and central retinal vein occlusion (CRVO). Methods. Twelve patients from a single clinics day qualified for intravitreal injections (ARMD n = 6, DME n = 3, CRVO n = 3) and underwent a combination treatment including a single-site 23 gauge core vitrectomy which yielded a volume of 0.6 mL undiluted vitreous per patient. Interleukin-6 (IL-6), vascular endothelial growth factor isoform A (VEGF-A), and monocyte chemo-attractant protein-1 (MCP-1) were assessed directly from 0.3 mL at the same day (fresh samples). To assess the reproducibility 0.3 ml were frozen for 60 days at -80°, on which the CBA was repeated (frozen samples). Results. In the fresh samples IL-6 was highest in CRVO (median IL-6 55.8 pg/mL) > DME (50.6) > ARMD (3.1). Highest VEGF was measured in CRVO (447.4) > DME (3.9) > ARMD (2.0). MCP-1 was highest in CRVO (595.7) > AMD (530.8) > DME (178). The CBA reproducibility after frozen storage was examined to be most accurate for MCP1 (P = 0.91) > VEGF (P = 0.68) > IL-6 (P = 0.49). Conclusions. CBA is an innovative, fast determining, and reliable technology to analyze proteins in fluids, like the undiluted vitreous, which is important to better understand ocular pathophysiology and pharmacology. There is no influence of intermittent storage at -80° for the reproducibility of the CBA

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broad-scale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other data sets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts

Invasive alien species in the food chain : advancing risk assessment models to address climate change, economics and uncertainty

Economic globalization depends on the movement of people and goods between countries. As these exchanges increase, so does the potential for translocation of harmful pests, weeds, and pathogens capable of impacting our crops, livestock and natural resources (Hulme 2009), with concomitant impacts on global food security (Cook et al. 2011)

Correlation from undiluted vitreous cytokines of untreated central retinal vein occlusion with spectral domain optical coherence tomography

Purpose: To correlate inflammatory and proangiogenic key cytokines from undiluted vitreous of treatment-naïve central retinal vein occlusion (CRVO) patients with SD-OCT parameters. Methods: Thirty-five patients (age 71.1 years, 24 phakic, 30 nonischemic) underwent intravitreal combination therapy, including a single-site 23-gauge core vitrectomy. Twenty-eight samples from patients with idiopathic, non-uveitis floaterectomy served as controls. Interleukin 6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and vascular endothelial growth factor (VEGF-A) levels were correlated with the visual acuity (logMar), category of CRVO (ischemic or nonischemic) and morphologic parameters, such as central macular thickness-CMT, thickness of neurosensory retina-TNeuro, extent of serous retinal detachment-SRT and disintegrity of the IS/OS and others. Results: The mean IL-6 was 64.7pg/ml (SD ± 115.8), MCP-1 1015.7 ( ± 970.1), and VEGF-A 278.4 ( ± 512.8), which was significantly higher than the control IL-6 6.2 ± 3.4pg/ml (P=0.06), MCP-1 253.2 ± 73.5 (P<0.0000001) and VEGF-A 7.0 ± 4.9 (P<0.0006). All cytokines correlated highly with one another (correlation coefficient r=0.82 for IL-6 and MCP-1; r=0.68 for Il-6 and VEGF-A; r=0.64 for MCP-1 and VEGF-A). IL-6 correlated significantly with CMT, TRT, SRT, dIS/OS, and dELM. MCP-1 correlated significantly with SRT, dIS/OS, and dELM. VEGF-A correlated not with changes in SD-OCT, while it had a trend to be higher in the ischemic versus the nonischemic CRVO group (P=0.09). Conclusions: The inflammatory cytokines were more often correlated with morphologic changes assessed by SD-OCT, whereas VEGF-A did not correlate with CRVO-associated changes in SD-OCT. VEGF inhibition alone may not be sufficient in decreasing the inflammatory response in CRVO therapy

A Combined Score of Circulating miRNAs Allows Outcome Prediction in Critically Ill Patients

Background and aims: Identification of patients with increased risk of mortality represents an important prerequisite for an adapted adequate and individualized treatment of critically ill patients. Circulating micro-RNA (miRNA) levels have been suggested as potential biomarkers at the intensive care unit (ICU), but none of the investigated miRNAs displayed a sufficient sensitivity or specificity to be routinely employed as a single marker in clinical practice. Methods and results: We recently described alterations in serum levels of 7 miRNAs (miR-122, miR-133a, miR-143, miR-150, miR-155, miR-192, and miR-223) in critically ill patients at a medical ICU. In this study, we re-analyzed these previously published data and performed a combined analysis of these markers to unravel their potential as a prognostic scoring system in the context of critical illness. Based on the Youden’s index method, cut-off values were systematically defined for dysregulated miRNAs, and a “miRNA survival score” was calculated. Patients with high scores displayed a dramatically impaired prognosis compared to patients with low values. Additionally, the predictive power of our score could be further increased when the patient’s age was additionally incorporated into this score. Conclusions: We describe the first miRNA-based biomarker score for prediction of medical patients’ outcome during and after ICU treatment. Adding the patients’ age into this score was associated with a further increase in its predictive power. Further studies are needed to validate the clinical utility of this score in risk-stratifying critically ill patients

Predicting cannabis cultivation on national forests using a rational choice framework

Government agencies in the United States eradicated 10.3 million cannabis plants in 2010. Most (94%) of these plants were outdoor-grown, and 46% of those were discovered on federal lands, primarily on national forests in California, Oregon, and Washington. We developed models that reveal how drug markets, policies, and environmental conditions affect grow siting decisions. The models were built on a rational choice theoretical structure, and utilized data describing 2322 cannabis grow locations (2004–2012) and 9324 absence locations in the states\u27 national forests. Predictor variables included cannabis market prices, law enforcement density, and socioeconomic, demographic, and environmental variables.We also used the models to construct regional maps of grow site likelihood. Significant predictors included marijuana street price and variables associated with grow site productivity (e.g., elevation and proximity to water), production costs, and risk of discovery. Overall, the pattern of grow site establishment on national forests is consistent with rational choice theory. In particular, growers consider cannabis prices and law enforcement when selecting sites. Ongoing adjustments in state cannabis laws could affect cultivation decisions on national forests. Any changes in cannabis policies can be reflected in our models to allow agencies to redirect interdiction resources and potentially increase discovery success

Predicting cannabis cultivation on national forests using a rational choice framework

Government agencies in the United States eradicated 10.3 million cannabis plants in 2010. Most (94%) of these plants were outdoor-grown, and 46% of those were discovered on federal lands, primarily on national forests in California, Oregon, and Washington. We developed models that reveal how drug markets, policies, and environmental conditions affect grow siting decisions. The models were built on a rational choice theoretical structure, and utilized data describing 2322 cannabis grow locations (2004–2012) and 9324 absence locations in the states\u27 national forests. Predictor variables included cannabis market prices, law enforcement density, and socioeconomic, demographic, and environmental variables.We also used the models to construct regional maps of grow site likelihood. Significant predictors included marijuana street price and variables associated with grow site productivity (e.g., elevation and proximity to water), production costs, and risk of discovery. Overall, the pattern of grow site establishment on national forests is consistent with rational choice theory. In particular, growers consider cannabis prices and law enforcement when selecting sites. Ongoing adjustments in state cannabis laws could affect cultivation decisions on national forests. Any changes in cannabis policies can be reflected in our models to allow agencies to redirect interdiction resources and potentially increase discovery success

Spread of common native and invasive grasses and ruderal trees following anthropogenic disturbances in a tropical dry forest

Introduction A fundamental challenge to the integrity of tropical dry forest ecosystems is the invasion of non-native grass species. These grasses compete for resources and fuel anthropogenic wildfires. In 2012, a bulldozer from the Puerto Rico Electric Power Authority cleared a 570-m trail from a state road into a mature dry forest section of Guánica Forest to control a wildfire. We monitored colonization by a non-native invasive grass (Megathyrsus maximus), a highly invasive tree (Leucaena leucocephala), and a native grass (Uniola virgata), as well as natural regeneration, along the bulldozer trail. We determined whether bulldozing facilitated colonization by these species into the forest and the extent of spread. Results Distance from propagule source and temporal variations strongly influenced colonization by our three focal species. Megathyrsus maximus invaded along the trail from source populations by the state road. The establishment of new colonies of M. maximus seedlings went as far as 570 m inside the forest (i.e., at the end of the bulldozer trail), but we found most new colonies within 270 m of the road. Leucaena leucocephala exhibited a similar spreading pattern. Before disturbance, Uniola virgata was distributed widely across the forest, but the highest densities were found in areas near the latter portion (\u3e 401 m) of the bulldozer trail. Subsequently, the species formed new clumps along more than half of the trail (250 to 570 m), apparently colonizing from undisturbed patches nearby. Conclusions Bulldozing facilitated the invasion of non-native vegetation. The projected community assemblage will be more fire-prone than before since M. maximus carries fire across the landscape better than U. virgata, emphasizing the capacity of invasive plant colonization to alter local ecological processes after only a single wildfire and bulldoze event. Our results provide a valuable baseline for short-term vegetation response to anthropogenic disturbances in tropical semi-deciduous dry forests