Thus, the gap between the supposed resistance gene Cyp6g1 and the observed resistance phenomenon was closed by the evidence that CYP6G1 is capable of metabolising at least two insecticides.

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Oligoclase and labradorite crystals have been experimentally replaced by albite in an aqueous sodium silicate solution at 600°C and 2 kbars. The replacement is pseudomorphic and is characterised by a sharp chemical interface which progresses through the feldspar while preserving the crystallographic orientation. Reaction rims of albite, up to 50 lm thick, can be readily achieved within 14 days. Re-equilibration of plagioclase in an 18 O-enriched sodium-and silica-bearing solution results in oxygen isotope redistribution within the feldspar framework structure. The observed characteristics of the reaction products are similar to naturally albitised plagioclase and are indicative of an interface-coupled dissolution-reprecipitation mechanism. Chemical analyses demonstrate that the albitisation is accompanied by the mobilisation of major, minor and trace elements also including elements such as Al and Ti which are commonly regarded as immobile during hydrothermal alteration. The results contribute to developing our understanding of the close association between large-scale albitisation and secondary ore mineralisation which is common in nature.

The estimation of the peak metamorphic temperature by Raman spectroscopy of carbonaceous material (RSCM) is influenced by several bias sources grouped in measuring conditions, spectral processing and sample heterogeneity. The measuring conditions (selected excitation wavelength) and the operator bias during spectral processing have a pronounced impact on the temperature estimate and thus on the comparability and portability of thermometric data obtained by RSCM. Several calibration lines of RSCM geothermometers are published already, but no standardised approach exists. Samples of carbonaceous material bearing metasediments with well‐established metamorphic conditions of the central and western Alps compile a reference series. By applying an automated, iterative and randomised curve‐fitting approach, a consistent and user input‐independent RSCM geothermometer is presented, which covers peak metamorphic temperatures from ca. 160 to 600 °C. The method is hardware independent because the measuring conditions bias is excluded by the use of the reference series and the automated curve‐fitting approach reduces the spectral processing bias effectively, increasing the method's comparability and portability. By distributing the reference series and the automated curve‐fitting software, a laboratory will be able to derive a laboratory specific calibration line for the RSCM geothermometer.

Raman spectroscopy of carbonaceous material (RSCM) is frequently used to determine metamorphic peak temperatures from the structural order of carbonaceous material enclosed in metasediments. This method provides a quick, robust and relatively cheap geothermometer. However, the comparability of the RSCM parameter is low as there are at least three major sources of biasing factors. These sources are the spectral curve-fitting procedure, the sample characteristics itself and the experimental design including the used Raman system. To assess the impacts of the biasing factors on RSCM, a series of experiments was performed. The experiments showed that curve-fitting is strongly influenced by individual operator-bias and the degrees of freedom in the model, implying the need for a standardised curve-fitting procedure. Due to the diversity of components (optics, light detection device, gratings, etc.) and their combinations within the Raman systems, different Raman instruments generally give differing results. Consequently, to estimate comparable metamorphic temperatures from RSCM data, every Raman instrument needs its own calibration. This demands a reference material series that covers the entire temperature calibration range. Although sample heterogeneity will still induce some variation, a reference material series combined with standardised curve-fitting procedures will significantly increase the overall comparability of RSCM data from different laboratories.