A comparison of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast MrI with and without contrast agent leakage correction in paediatric brain tumours

OBJECTIVE: To investigate correlations between MRI perfusion metrics measured by dynamic susceptibility contrast and arterial spin labelling in paediatric brain tumours. METHODS: 15 paediatric patients with brain tumours were scanned prospectively using pseudo-continuous arterial spin labelling (ASL) and dynamic susceptibility contrast (DSC-) MRI with a pre-bolus to minimise contrast agent leakage. Cerebral blood flow (CBF) maps were produced using ASL. Cerebral blood volume (CBV) maps with and without contrast agent leakage correction using the Boxerman technique and the leakage parameter, K2, were produced from the DSC data. Correlations between the metrics produced were investigated. RESULTS: Histology resulted in the following diagnoses: pilocytic astrocytoma (n = 7), glioblastoma (n = 1), medulloblastoma (n = 1), rosette-forming glioneuronal tumour of fourth ventricle (n = 1), atypical choroid plexus papilloma (n = 1) and pilomyxoid astrocytoma (n = 1). Three patients had a non-invasive diagnosis of low-grade glioma. DSC CBV maps of T1-enhancing tumours were difficult to interpret without the leakage correction. CBV values obtained with and without leakage correction were significantly different (p < 0.01). A significant positive correlation was observed between ASL CBF and DSC CBV (r = 0.516, p = 0.049) which became stronger when leakage correction was applied (r = 0.728, p = 0.002). K2 values were variable across the group (mean = 0.35, range = −0.49 to 0.64). CONCLUSION: CBV values from DSC obtained with and without leakage correction were significantly different. Large increases in CBV were observed following leakage correction in highly T1-enhancing tumours. DSC and ASL perfusion metrics were found to correlate significantly in a range of paediatric brain tumours. A stronger relationship between DSC and ASL was seen when leakage correction was applied to the DSC data. Leakage correction should be applied when analysing DSC data in enhancing paediatric brain tumours. ADVANCES IN KNOWLEDGE: We have shown that leakage correction should be applied when investigating enhancing paediatric brain tumours using DSC-MRI. A stronger correlation was found between CBF derived from ASL and CBV derived from DSC when a leakage correction was employed

Fat Hypertrophy as a Complication of Fat Transfer for Hemifacial Atrophy

Fat hypertrophy is a less commonly known complication of autologous fat transfer. We present a 32-year-old female with left hemifacial atrophy associated with systemic sclerosis, who was treated with 7 fat transfer procedures to correct the facial asymmetry. A total of 236.5 mL of fat was injected to the hemiface over a 4-year period to achieve good symmetry. A progressively enlarging, painless, soft mass over the left parotid region was noted at 3 months after the final fat transfer procedure. Magnetic resonance imaging showed a markedly enlarged bulk of subcutaneous fat over the left cheek with no evidence of necrosis, edema, or pathologic enhancement. Concurrent weight gain was noted secondary to additional nutritional input. The patient's aesthetic, symptomatic, and functional concerns led to the subsequent removal of 115 mL fat by liposuction. LEVEL OF EVIDENCE: 5

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (\-16%) and pasture (\-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence. © 2012 by the Ecological Society of America

Increasing phenological asynchrony between spring green-up and arrival of migratory birds

Consistent with a warming climate, birds are shifting the timing of their migrations, but it remains unclear to what extent these shifts have kept pace with the changing environment. Because bird migration is primarily cued by annually consistent physiological responses to photoperiod, but conditions at their breeding grounds depend on annually variable climate, bird arrival and climate-driven spring events would diverge. We combined satellite and citizen science data to estimate rates of change in phenological interval between spring green-up and migratory arrival for 48 breeding passerine species across North America. Both arrival and green-up changed over time, usually in the same direction (earlier or later). Although birds adjusted their arrival dates, 9 of 48 species did not keep pace with rapidly changing green-up and across all species the interval between arrival and green-up increased by over half a day per year. As green-up became earlier in the east, arrival of eastern breeding species increasingly lagged behind green-up, whereas in the west—where green-up typically became later—birds arrived increasingly earlier relative to green-up. Our results highlight that phenologies of species and trophic levels can shift at different rates, potentially leading to phenological mismatches with negative fitness consequences

Mycobial community assemblages in sink drains across a university campus

Multiple fungal species, including potential opportunistic pathogens have been previously identified in water systems. Here, we investigated over 250 restroom sink fungal communities across a university campus and evaluated their diversity and core taxa present. Remarkable similarity in mycobial community composition was observed across buildings with Ascomycota consistently dominating. We found a core mycobiome independent of the building sampled, that included Exophiala species, potential opportunistic pathogenic black yeasts. Other prevalent and dominant taxa included Saccharomyces and Fusarium, common built environment fungi. The frequent presence of Malassezia, a common skin commensal, showed the external influence of human activities as a source of fungi to sinks. The study represents a novel exploration of sink P-traps mycobial communities from a public area and highlights their importance as reservoirs of possible pathogenic fungi, as well as emphasizing the relevance of further research in this understudied ecosystem within the built environment

A Genome-Wide Approach to Discovery of Small RNAs Involved in Regulation of Virulence in Vibrio cholerae

Small RNAs (sRNAs) are becoming increasingly recognized as important regulators in bacteria. To investigate the contribution of sRNA mediated regulation to virulence in Vibrio cholerae, we performed high throughput sequencing of cDNA generated from sRNA transcripts isolated from a strain ectopically expressing ToxT, the major transcriptional regulator within the virulence gene regulon. We compared this data set with ToxT binding sites determined by pulldown and deep sequencing to identify sRNA promoters directly controlled by ToxT. Analysis of the resulting transcripts with ToxT binding sites in cis revealed two sRNAs within the Vibrio Pathogenicity Island. When deletions of these sRNAs were made and the resulting strains were competed against the parental strain in the infant mouse model of V. cholerae colonization, one, TarB, displayed a variable colonization phenotype dependent on its physiological state at the time of inoculation. We identified a target of TarB as the mRNA for the secreted colonization factor, TcpF. We verified negative regulation of TcpF expression by TarB and, using point mutations that disrupted interaction between TarB and tpcF mRNA, showed that loss of this negative regulation was primarily responsible for the colonization phenotype observed in the TarB deletion mutant

Ethanol reversal of tolerance to the respiratory depressant effects of morphine

Opioids are the most common drugs associated with unintentional drug overdose. Death results from respiratory depression. Prolonged use of opioids results in the development of tolerance but the degree of tolerance is thought to vary between different effects of the drugs. Many opioid addicts regularly consume alcohol (ethanol), and post-mortem analyses of opioid overdose deaths have revealed an inverse correlation between blood morphine and ethanol levels. In the present study, we determined whether ethanol reduced tolerance to the respiratory depressant effects of opioids. Mice were treated with opioids (morphine, methadone, or buprenorphine) for up to 6 days. Respiration was measured in freely moving animals breathing 5% CO(2) in air in plethysmograph chambers. Antinociception (analgesia) was measured as the latency to remove the tail from a thermal stimulus. Opioid tolerance was assessed by measuring the response to a challenge dose of morphine (10 mg/kg i.p.). Tolerance developed to the respiratory depressant effect of morphine but at a slower rate than tolerance to its antinociceptive effect. A low dose of ethanol (0.3 mg/kg) alone did not depress respiration but in prolonged morphine-treated animals respiratory depression was observed when ethanol was co-administered with the morphine challenge. Ethanol did not alter the brain levels of morphine. In contrast, in methadone- or buprenorphine-treated animals no respiratory depression was observed when ethanol was co-administered along with the morphine challenge. As heroin is converted to morphine in man, selective reversal of morphine tolerance by ethanol may be a contributory factor in heroin overdose deaths

Perspectives on Risk Perceptions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72341/1/j.1539-6924.1981.tb01409.x.pd

The use of the Kalman filter in the automated segmentation of EIT lung images

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (−16%) and pasture (−13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.Keywords: urban growth, econometric modeling, forest, land-use scenarios, ecosystem services, land-use change, ecoregions, net returnsKeywords: urban growth, econometric modeling, forest, land-use scenarios, ecosystem services, land-use change, ecoregions, net return