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Träfflista för sökning "WFRF:(Posselt J.) srt2:(2020-2022)"

Sökning: WFRF:(Posselt J.) > (2020-2022)

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1.
  • Jaeger, Anna, et al. (författare)
  • Transformation of organic micropollutants along hyporheic flow in bedforms of river-simulating flumes
  • 2021
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Urban streams receive increasing loads of organic micropollutants from treated wastewaters. A comprehensive understanding of the in-stream fate of micropollutants is thus of high interest for water quality management. Bedforms induce pumping effects considerably contributing to whole stream hyporheic exchange and are hotspots of biogeochemical turnover processes. However, little is known about the transformation of micropollutants in such structures. In the present study, we set up recirculating flumes to examine the transformation of a set of micropollutants along single flowpaths in two triangular bedforms. We sampled porewater from four locations in the bedforms over 78 days and analysed the resulting concentration curves using the results of a hydrodynamic model in combination with a reactive transport model accounting for advection, dispersion, first-order removal and retardation. The four porewater sampling locations were positioned on individual flowpaths with median solute travel times ranging from 11.5 to 43.3 h as shown in a hydrodynamic model previously. Highest stability was estimated for hydrochlorothiazide on all flowpaths. Lowest detectable half-lives were estimated for sotalol (0.7 h) and sitagliptin (0.2 h) along the shortest flowpath. Also, venlafaxine, acesulfame, bezafibrate, irbesartan, valsartan, ibuprofen and naproxen displayed lower half-lives at shorter flowpaths in the first bedform. However, the behavior of many compounds in the second bedform deviated from expectations, where particularly transformation products, e.g. valsartan acid, showed high concentrations. Flowpath-specific behavior as observed for metformin or flume-specific behavior as observed for metoprolol acid, for instance, was attributed to potential small-scale or flume-scale heterogeneity of microbial community compositions, respectively. The results of the study indicate that the shallow hyporheic flow field and the small-scale heterogeneity of the microbial community are major controlling factors for the transformation of relevant micropollutants in river sediments.
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2.
  • Markmann, James F., et al. (författare)
  • Phase 3 trial of human islet-after-kidney transplantation in type 1 diabetes
  • 2021
  • Ingår i: American Journal of Transplantation. - : John Wiley & Sons. - 1600-6135 .- 1600-6143. ; 21:4, s. 1477-1492
  • Tidskriftsartikel (refereegranskat)abstract
    • Allogeneic islet transplant offers a minimally invasive option for beta cell replacement in the treatment of type 1 diabetes (T1D). The CIT consortium trial of purified human pancreatic islets (PHPI) in patients with T1D after kidney transplant (CIT06), a National Institutes of Health-sponsored phase 3, prospective, open-label, single-arm pivotal trial of PHPI, was conducted in 24 patients with impaired awareness of hypoglycemia while receiving intensive insulin therapy. PHPI were manufactured using standardized processes. PHPI transplantation was effective with 62.5% of patients achieving the primary endpoint of freedom from severe hypoglycemic events and HbA(1c) <= 6.5% or reduced by >= 1 percentage point at 1 year posttransplant. Median HbA(1c)declined from 8.1% before to 6.0% at 1 year and 6.3% at 2 and 3 years following transplant (P < .001 for all vs baseline), with related improvements in hypoglycemia awareness and glucose variability. The improved metabolic control was associated with better health-related and diabetes-related quality of life. The procedure was safe and kidney allograft function remained stable after 3 years. These results add to evidence establishing allogeneic islet transplant as a safe and effective treatment for patients with T1D and unstable glucose control despite intensive insulin treatment, supporting the indication for PHPI in the post-renal transplant setting.
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3.
  • Vukicevic, T., et al. (författare)
  • Sensitivity of Modeled Microphysics to Stochastically Perturbed Parameters
  • 2022
  • Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:7
  • Tidskriftsartikel (refereegranskat)abstract
    • This study examines the characteristics of several model parameter perturbation methodologies for ensemble simulations of cloud microphysical processes in convection. A simplified 1D model is used to focus the results on cloud microphysics without the complication of feedbacks to the dynamics and environment. Several parameter perturbation methods are tested, including non-stochastic and stochastic with various distributions and parameter covariance. We find that an ensemble comprised of different time-invariant parameters (non-stochastic) exhibits little bias, but small spread. In addition, its behavior does not respect the time evolution of convection through its various phases. Stochastic parameter (SP) methods in which no inter-parameter covariance is applied produce greater spread, but significant bias. The bias is particularly large for lognormal parameter perturbation distributions. The ensemble spread is retained and the bias reduced when time-varying parameter covariance is applied. In this case, the SP scheme is able to adapt to the time and state-dependent covariance structures and produce ensemble characteristics that are consistent with the specific microphysical processes operating at any given time. The results suggest that SP schemes would benefit from inclusion of parameter covariances, and specifically those that vary with the state of the system. It also suggests that a Normal or LogNormal SP scheme with no covariance may significantly impact the ensemble bias. Finally, the results indicate that high temporal and spatial resolution observations may be needed to characterize the variability in parameter values and covariance.
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