| 1. |
- Harding, R, et al.
(author)
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Climate feedbacks at the tundra-taiga interface
- 2002
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In: Ambio: a Journal of Human Environment. - 0044-7447. ; :Sp. Iss. 12, s. 47-55
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Journal article (peer-reviewed)abstract
- Feedbacks, or internal interactions, play a crucial role in the climate system. Negative feedback will reduce the impact of an external perturbation, a positive feedback will amplify the effect and could lead to an unstable system. Many of the feedbacks found in the climate system are positive; thus, for example, increasing CO2 levels will increase temperature, reduce the snow cover, increase the absorption of radiation and hence increase temperature further. The most obvious feedbacks, such as the snow example quoted above, are already included within our models of the climate and earth system. Others, such as the impact of increasing forest cover due to global warming, are only just being included. Others, such as, the impact of global warming on the northern peatlands and the impact of freshwater flows on the Arctic Ocean are not yet considered. The contrast in surface characteristics between low tundra vegetation to high taiga forest is considerable. The contrast is greatest in the winter, when the tundra is snow covered but the trees of the taiga protrude through the snow pack, and is probably the greatest contrast found on the land surface anywhere. This variation causes massive changes in the energy fluxes at the surface and hence the temperature conditions on the ground and within the atmosphere. There will be large resultant changes in the vegetation development, the carbon fluxes, the permafrost and the hydrology. The Arctic is already experiencing change and it is essential for us to understand the basic processes, and how these interact, to be confident of our predictions of environmental change in the future.
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| 2. |
- Winick, Jeremy R., et al.
(author)
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Thermospheric infrared radiance response to the April 2002 geomagnetic storm from SABER infrared and GUVI ultraviolet limb data
- 2004
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In: Proceedings of SPIE, the International Society for Optical Engineering. - : SPIE. - 0277-786X .- 1996-756X. ; 5235, s. 250-263
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Journal article (peer-reviewed)abstract
- The SABER instrument on TIMED continuously measures certain infrared limb radiance profiles with unprecedented sensitivity. Among these are emissions of CO 2 v 3 at 4.3 μm, routinely recorded to tangent heights of ∼140-150 km, and NO at 5.3 μm, seen to above 200 km. Both of these are greatly enhanced during periods of strong auroral activity, when they can be measured to ∼200 km and ∼300 km, respectively. We use these infrared channels of SABER and coincident far ultraviolet (FUV) measurements from GUVI on TIMED, to study the geomagnetic storm of April 2002. These all give a consistent measure of auroral energy input into the lower thermosphere at high latitudes. Emission in yet another SABER channel, near 2.0 μm, correlates well with enhanced electron energy deposition. We also have, in the 5.3-μm emissions from the long-lived population of aurorally produced NO, a tracer of how this energy is transported equatorward and released over an extended period of time, a few days. In this paper, we discuss the global patterns of energy deposition into the expanded auroral oval, its transport to lower latitudes, and its loss as revealed by the NO 5.3-μm emissions.
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| 3. |
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| 4. |
- Look, M, et al.
(author)
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Pooled analysis of prognostic impact of uPA and PAI-I in breast cancer patients
- 2003
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In: Thrombosis and Haemostasis. - 0340-6245. ; 90:3, s. 538-548
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Journal article (peer-reviewed)abstract
- In this report we present an extension of the pooled analysis of the prognostic impact of urokinase-type plasminogen activator (uPA) and its inhibitor PAI-I in breast cancer patients. We analyzed a different endpoint, metastasis-free survival (MFS). We checked the consistency of the estimates for uPA and PAI-I for relapse-free survival (RFS) and MFS exploring possible sources of heterogeneity. Nodal status, the most important prognostic factor for breast cancer, introduced heterogeneity in the uPA/PAI-I survival analyses, reflecting the interaction between nodal status and uPA/PAI-I. The estimates for uPA and PAI-I were found to be consistent, even when a different transformation of their values was used. The heterogeneity of the separate data sets decreased if the levels of uPA and PAI-I were ranked, data sets were pooled, and the analyses corrected for the base model that included all traditional prognostic factors, and stratified by data set. We conclude that uPA and PAI-I are ready to be used in the clinic to help classify breast cancer patients into high and low risk groups.
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| 5. |
- Look, MP, et al.
(author)
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Pooled analysis of prognostic impact of urokinase-type plasminogen activator and its inhibitor PAI-1 8377 breast cancer patients
- 2002
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 94:2, s. 116-128
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Journal article (peer-reviewed)abstract
- Background: Urokinase-type plasminogen activator (uPA) and its inhibitor (PAI-1) play essential roles in tumor invasion and metastasis. High levels of both uPA and PAT-1 are associated with poor prognosis in breast cancer patients. To confirm the prognostic value of uPA and PAI-1 in primary breast cancer, we reanalyzed individual patient data provided by members of the European Organization for Research and Treatment of Cancer-Receptor and Biomarker Group (EORTC-RBG). Methods: The study included 18 datasets involving 8377 breast cancer patients. During follow-up (median 79 months), 35% of the patients relapsed and 27% died. Levels of uPA and PAI-1 in tumor tissue extracts were determined by different immunoassays; values were ranked within each dataset and divided by the number of patients in that dataset to produce fractional ranks that could be compared directly across datasets. Associations of ranks of uPA and PAI-1 levels with relapse-free survival (RFS) and overall survival (OS) were analyzed by Cox multivariable regression analysis stratified by dataset, including the following traditional prognostic variables: age, menopausal status, lymph node status, tumor size, histologic grade, and steroid hormone-receptor status. All P values were two-sided. Results: Apart from lymph node status, high levels of uPA and PAI-1 were the strongest predictors of both poor RFS and poor OS in the analyses of all patients. Moreover, in both lymph node-positive and lymph nodenegative patients, higher uPA and PAI-1 values were independently associated with poor RFS and poor OS. For (untreated) lymph node-negative patients in particular, uPA and PAI-1 included together showed strong prognostic ability (all P<.001). Conclusions: This pooled analysis of the EORTC-RBG datasets confirmed the strong and independent prognostic value of uPA and PAI-1 in primary breast cancer. For patients with lymph node-negative breast cancer, uPA and PAI-1 measurements in primary tumors may be especially useful for designing individualized treatment strategies.
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