Protein kinase Cµ (PKCµ) represents a new subtype of the PKC family characterized by the presence of a pleckstrin homology (PH) domain and an amino-terminal hydrophobic region. In order to analyse the potential role of PKCµ in signal-transduction pathways, stable PKCµ transfectants were established with human and murine cell lines. All transfectants showed a reduced sensitivity to tumor-necrosis-factor (TNF)-induced apoptosis, which correlated with the amount of transgene expressed and with an enhanced basal transcription rate of NF-κB-driven genes including the inhibitor of apoptosis protein 2 (cIAP2) and TNF-receptor-associated protein 1 (TRAF1). Sensitivity to apoptosis induced by the lipid mediator ceramide was unchanged in PKCµ transfectants. In support of a PKCµ action on NF-κB, we show enhancement and downregulation of TNF-induced expression of a NF-κB-dependent reporter gene by transient overexpression of wild-type and kinase-negative mutants of PKCµ, respectively. Interestingly, no significant changes were found in an electrophoretic mobility shift assay, indicative of PKCµ action downstream of IκB degradation, probably by modulation of the transactivation capacity of NF-κB. The dominant negative action of the kinase-negative mutant further suggest a regulatory role of PKCµ for NF-κB-dependent gene expression.Keywords : Protein kinase Cµ; nuclear factor-κB activation; apoptosis protection.The protein kinases C (PKC) comprise a family of intracellular serine/threonine-specific kinases with currently 11 molecularly defined members, that are considered to be important regulatory enzymes of diverse cellular processes [1,2]. Based on the primary structure and in vitro activation requirements, the PKC family can be grouped into three major classes; Ca 2ϩ -dependent classical PKCs (cPKCA, β1, β2 and γ), Ca 2ϩ -independent, novel PKCs (nPKCε, δ, η and θ) and atypical PKCs (PKCζ, λ/ι). The recently identified PKCµ and its mouse homologue PKD do not conform to either one of these major classes and may thus define a new subgroup [3,4]. The lack of a typical pseudosubstrate site, the presence of two amino terminal hydrophobic domains and a pleckstrin homology (PH) domain within the regulatory region are characteristic and unique features of the PKCµ/PKD subgroup of PKCs [5].PKCµ is ubiquitiously expressed and first evidence for involvement in diverse cellular functions stems from reports showing enhancement of constitutive transport processes in PKCµ-overexpressing epithelial cells [6] and PKCµ activation during antigen-receptor-mediated signalling in B cells [7]. Aside from these initial observations in selected cell lines, the role and biological importance of PKCµ for intracellular signal processes and, in particular, identification of its extracellular activators and mode of activation are to date largely undefined.Typically, PKC activity is regulated by lipid second messengers, predominantly diacylglycerol [1], but also other lipid mediators such as ceramide, arachidonic or phosphatidic acid and phosphatidylin...

Domestic wells in North America and elsewhere are typically constructed at relatively shallow depths and with the sand or gravel pack extending far above the intake screen of the well (shallow well seal). The source areas of these domestic wells and the effect of an extended gravel pack on the source area are typically unknown, and few resources exist for estimating these. In this article, we use detailed, high-resolution ground water modeling to estimate the capture zone (source area) of a typical domestic well located in an alluvial aquifer. Results for a wide range of aquifer and gravel pack hydraulic conductivities are compared to a simple analytical model. Correction factors for the analytical model are computed based on statistical regression of the numerical results against the analytical model. This tool can be applied to estimate the source area of a domestic well for a wide range of conditions. We show that an extended gravel pack above the well screen may contribute significantly to the overall inflow to a domestic well, especially in less permeable aquifers, where that contribution may range from 20% to 50% and that an extended gravel pack may lead to a significantly elongated capture zone, in some instances, nearly doubling the length of the capture zone. Extending the gravel pack much above the intake screen therefore significantly increases the vulnerability of the water source.

Abstract. Non-stationary and non-linear dynamic time series analysis tools are applied to multi-annual eddy covariance and micrometeorological data from 44 FLUXNET sites to derive a light use efficiency model for gross primary production on a daily basis. The extracted typical behaviour of the canopies in response to meteorological forcing leads to a model formulation allowing for a variable influence of the environmental drivers temperature and moisture availability modulating the light use efficiency. Thereby, the model is applicable to a broad range of vegetation types and climatic conditions. The proposed model explains large proportions of the variation of the gross carbon uptake at the study sites while the optimized set of six parameters is well defined. With the parameters showing explainable and meaningful relations to site-specific environmental conditions, the model has the potential to serve as basis for general regionalization strategies for large scale carbon flux predictions.

To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.