Mycobacteria and fungi in moisture-damaged building materials

In contrast to the growth of fungi, the growth of mycobacteria in moisture-damaged building materials has rarely been studied. Environmental mycobacteria were isolated from 23% of samples of moisture-damaged materials (n = 88). The occurrence of mycobacteria increased with increasing concentrations of fungi. Mycobacteria may contribute to indoor exposure and associated adverse health effects.     

A large carbon pool and small sink in boreal Holocene lake sediments

Model‐based estimates suggest that lake sediments may be a significant, long‐term sink for organic carbon (C) at regional to global scales. These models have used various approaches to predict sediment storage at broad scales from very limited data sets. Here, we report a large‐scale direct assessment of the standing stock and sedimentation rate of C for a representative set of lakes in Finland. The 122 lakes were selected from the statistically selected Nordic Lake Survey database, they cover the entire country and the water quality represents the average lake water quality in Finland. Unlike all prior estimates, these data use sediment cores that comprise the entire sediment record. The data show that within Finland, aquatic ecosystems contain the second largest areal C stocks (19 kg C m^?2) after peatlands (72 kg C m^?2), and exceed by significant amounts stocks in the forest soil (uppermost 75cm; 7.2 kg C m^?2) and woody biomass (3.4 kg C m^?2). Kauppi et al. (1997). The Finnish estimate extrapolated over the boreal region gives a total C pool in lakes 19–27 Pg C, significantly lower than the previous model‐based estimates.     

Midsummer spatial variation in methane efflux from stands of littoral vegetation in a boreal meso-eutrophic lake

1. Spatial variation of methane (CH₄) efflux from the littoral zone of a meso‐eutrophic boreal lake was studied with a closed‐chamber technique for three summer days in 22 vegetation stands, consisting of three emergent and three floating‐leaved species. 2. Between‐species differences in CH₄ emission were significant. The highest emissions were measured from the emergent Phragmites australis stands (0.5–1.7 mmol m^?2 h^?1), followed by Schoenoplectus lacustris > Equisetum fluviatile > Nuphar lutea > Sparganium gramineum > Potamogeton natans. Within‐species differences between stands were not significant. 3. In P. australis stands, the stand‐specific mean CH₄ emission was significantly correlated with solar radiation, probably indicating the role of effective pressurised ventilation on CH₄ fluxes. The proportion of net primary production emitted as CH₄ was significantly higher in P. australis stands (7.4%) than in stands of S. lacustris and E. fluviatile (both 0.5%). 4. In N. lutea stands, CH₄ efflux was negatively correlated with the mean fetch and positively with the percentage cover of leaves on the water surface. There were no differences in CH₄ efflux between intact N. lutea leaves and those grazed by coleopteran Galerucella nymphaeae. In S. graminaeum and P. natans stands, CH₄ effluxes were not related to any of the measured environmental variables. 5. For all vegetation stands, the biomass above water level explained about 60% of the observed spatial variation in CH₄ emission, indicating the important role of plants as gas conduits and producers of substrates for methanogens in the anoxic sediment.     

Simulation tools for biochemical networks: evaluation of performance and usability

MOTIVATION: Simulation of dynamic biochemical systems is receiving considerable attention due to increasing availability of experimental data of complex cellular functions. Numerous simulation tools have been developed for numerical simulation of the behavior of a system described in mathematical form. However, there exist only a few evaluation studies of these tools. Knowledge of the properties and capabilities of the simulation tools would help bioscientists in building models based on experimental data. RESULTS: We examine selected simulation tools that are intended for the simulation of biochemical systems. We choose four of them for more detailed study and perform time series simulations using a specific pathway describing the concentration of the active form of protein kinase C. We conclude that the simulation results are convergent between the chosen simulation tools. However, the tools differ in their usability, support for data transfer to other programs and support for automatic parameter estimation. From the experimentalists' point of view, all these are properties that need to be emphasized in the future.     

Mycobacteria in water and loose deposits of drinking water distribution systems in Finland

Drinking water distribution systems were analyzed for viable counts of mycobacteria by sampling water from waterworks and in different parts of the systems. In addition, loose deposits collected during mechanical cleaning of the main pipelines were similarly analyzed. The study covered 16 systems at eight localities in Finland. In an experimental study, mycobacterial colonization of biofilms on polyvinyl chloride tubes in a system was studied. The isolation frequency of mycobacteria increased from 35% at the waterworks to 80% in the system, and the number of mycobacteria in the positive samples increased from 15 to 140 CFU/liter, respectively. Mycobacteria were isolated from all 11 deposits with an accumulation time of tens of years and from all 4 deposits which had accumulated during a 1-year follow-up time. The numbers of mycobacteria were high in both old and young deposits (medians, 1.8 x 10(5) and 3.9 x 10(5) CFU/g [dry weight], respectively). Both water and deposit samples yielded the highest numbers of mycobacteria in the systems using surface water and applying ozonation as an intermediate treatment or posttreatment. The number and growth of mycobacteria in system waters correlated strongly with the concentration of assimilable organic carbon in the water leaving the waterworks. The densities of mycobacteria in the developing biofilms were highest at the distal sites of the systems. Over 90% of the mycobacteria isolated from water and deposits belonged to Mycobacterium lentiflavum, M. tusciae, M. gordonae, and a previously unclassified group of mycobacteria. Our results indicate that drinking water systems may be a source for recently discovered new mycobacterial species.     

Restoring volume,diversity and continuity of deadwood in boreal forests

Restoration of boreal forests by emulating natural disturbances is used to bring back typical components of natural forests that are reduced by silvicultural management. The volume, diversity and continuity of deadwood are the most important factors determining the diversity of deadwood-dependent species. In a large-scale experiment consisting of 43 experimental stands and 15 controls we assessed how alternative restoration methods enhancing deadwood availability (felling and felling + burning with two levels of felling: 20 and 40 % of initial volume of living trees, and a storm treatment) would affect short- and long-term deadwood volume and diversity using 7-year deadwood measurements and simulation modelling. In short-term, restoration by felling + burning increased both the volume and diversity of deadwood, whereas felling only increased merely the volume of deadwood. The simulations of tree growth, mortality and wood decomposition indicated that in comparison to controls, felled and storm-treated stands have greater deadwood volumes up to 40 years and felled + burned stands more than 60 years after restoration. Our results suggest that felling with 20 % of initial tree volume does not harm the future deadwood continuity, whereas intensive burning may imperil the deadwood continuity in a stand level. In conclusion, restoration clearly speeds up the development of the deadwood volumes needed to host large portions of biodiversity, and burning is the most effective restoration method in short- and long term. In practice, several restoration methods could be used concurrently in the landscape to obtain the best results.     

Long-term alcohol consumption and brown adipose tissue in man

The purpose of the present work was to study whether long-term alcohol consumption in man affects the development of brown adipose tissue. The adipose tissue around the thoracic aorta and common carotid arteries was collected at medicolegal autopsies on adults with a positive record of heavy alcohol consumption. Adults without any evident history of alcohol consumption served as controls. Histochemical reactions of the oxidative mitochondrial enzymes, cytochrome oxidase and succinate dehydrogenase were studied in samples of this adipose tissue and the activities of the enzymes were measured biochemically. There was histological evidence of some multilocular adipose tissue around the thoracic aorta and common carotid tissue from the non-drinkers was mostly unilocular resembling white adipose tissue. Histochemical evidence of brown adipose tissue was found in all alcohol consumers, but also in some of the controls. Biochemical cytochrome oxidase (CYO) and succinate dehydrogenase measurements in isolated mitochondria showed activity in 70% of the cases of drinkers and in one of the eight controls. Activity of CYO was measurable in the mitochondria from two other controls. The protein content of the samples from the alcoholics was twice that of the controls. The results suggest that chronic alcohol intake may induce a change in the white adipose tissue around the thoracic aorta and common carotid arteries of human adults into brown fat.     

Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences.