Lysosomal injury and MFO activity in the liver of flounder (Platichthys flesus L.) in relation to histopathology of hepatic degeneration and carcinogenesis

Flounder (Platichthys flesus L.), 18–48 cm total length were sampled in the mouth of the Elbe River during a 3-year interdisciplinary project ‘Fish Diseases in the Wadden Sea’. Lysosomal changes (lysosomal membrane stability) and the activity of biotransforming enzymes (MFOs/EROD) were measured parallel to investigations of ultrastructural changes in liver cells, tissue pathologies and macroscopically visible changes. The aim of the study was to investigate if these cyto- and biochemical parameters were able to reflect contaminant induced biological effects. Interlinking of the results of the MFO activity to the pathological alterations observed at the electron- and light-microscopic levels as well as during macroscopic inspection of identical individuals evidenced that the activity of the biotransformation enzymes (EROD) was not induced in healthy livers, increased considerably with the onset of liver changes and dropped again in those livers with degenerative, preneoplastic and neoplastic lesions. In contrast, concurrent studies of lysosomal membrane stability measured in parallel showed a decrease with the onset and progression of liver lesions from reversible to irreversible, neoplastic change.     

Implementation of high-order particle-tracking schemes in a water column model

Stochastic differential equations (SDEs) offer an attractively simple solution to complex transport-controlled problems, and have a wide range of physical, chemical, and biological applications, which are dominated by stochastic processes, such as diffusion. As for deterministic ordinary differential equations (ODEs), various numerical scheme exist for solving SDEs. In this paper various particle-tracking schemes are presented and tested for accuracy and efficiency (time vs. accuracy). To test the schemes, the particle tracking algorithms are implemented into a community wide used 1D water column model. Modelling individual particles allows a straightforward physical interpretation of the involved processes. Further, this approach is strictly mass conserving and does not suffer from the numerical diffusion that plagues grid-based methods. Moreover, the Lagrangian framework allows to assign properties to the individual particles, that can vary spatially and temporally. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection–diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field.The paper will show that especially the 2nd order schemes are accurate and highly efficient. At the same level of accuracy, the 2nd order scheme can be significantly faster than the 1st order counterpart. This gain in efficiency can be spent on a higher resolution for more accurate solutions at a lower cost.     

A method for detecting the diffusion of silver iodide particles in the atmosphere

Summary A technique is described which allows the study of the concentration of silver-iodide particles produced by a ground generator. It consists of marking these particles with Iodine 131, then filtering the air at the required places with air-borne filters. The iodine is extracted chemically, concentrated in a very small silver iodide disc which is then placed upon a nulcear emulsion. After two weeks the activity is measured by electron track counting. Limitations of the method are given.The paper has been published in extenso in the «Zeitschrift für angewandte Mathematik and Physik» (ZAMP), XIa, p. 375, 1958.     

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Spatial and temporal structure of the Denmark Strait Overflow revealed by acoustic observations

In spite of the fundamental role the Atlantic Meridional Overturning Circulation (AMOC) plays for global climate stability, no direct current measurement of the Denmark Strait Overflow, which is the densest part of the AMOC, has been available until recently that resolve the cross-stream structure at the sill for long periods. Since 1999, an array of bottom-mounted acoustic instruments measuring current velocity and bottom-to-surface acoustic travel times was deployed at the sill. Here, the optimization of the array configuration based on a numerical overflow model is discussed. The simulation proves that more than 80% of the dense water transport variability is captured by two to three acoustic current profilers (ADCPs). The results are compared with time series from ADCPs and Inverted Echo Sounders deployed from 1999 to 2003, confirming that the dense overflow plume can be reliably measured by bottom-mounted instruments and that the overflow is largely geostrophically balanced at the sill.     

Local air temperature tolerance: a sensible basis for estimating climate variability

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.