A Temporally Explicit Production Efficiency Model for Fuel Load Allocation in Southern Africa

Abstract We present a regional fuel load model (1 km² spatial resolution) applied in the southern African savanna region. The model is based on a patch-scale production efficiency model (PEM) scaled up to the regional level using empirical relationships between patch-scale behavior and multi-source remote sensing data (spatio-temporal variability of vegetation and climatic variables). The model requires the spatial distribution of woody vegetation cover, which is used to determine separate respiration rates for tree and grass. Net primary production, grass and tree leaf death, and herbivory are also taken into account in this mechanistic modeling approach. The fuel load model has been calibrated and validated from independent measurements taken from savanna vegetation in Africa southward from the equator. A sensitivity analysis on the effect of climate variables (incoming radiation, air temperature, and precipitation) has been conducted to demonstrate the strong role that water availability has in determining productivity and subsequent fuel load over the southern African region. The model performance has been tested in four different areas representative of a regional increasing rainfall gradient—Etosha National Park, Namibia, Mongu and Kasama, Zambia, as well as in Kruger National Park, South Africa. Within each area, we analyze model output from three different magnitudes of canopy coverage (<5, 30, and 50%). We find that fuel load ranges predicted by the model are globally in agreement with field measurements for the same year. High rainfall sustains green herbaceous production late in the dry season and delays tree leaf litter production. Effect of water on production varies across the rainfall gradient with delayed start of green material production in more arid regions.     

Conserved water-mediated H-bonding dynamics of catalytic Asn 175 in plant thiol protease

The role of invariant water molecules in the activity of plant cysteine protease is ubiquitous in nature. On analysing the 11 different Protein DataBank (PDB) structures of plant thiol proteases, the two invariant water molecules W1 and W2 (W220 and W222 in the template 1PPN structure) were observed to form H-bonds with the O_b atom of Asn 175. Extensive energy minimization and molecular dynamics simulation studies up to 2 ns on all the PDB and solvated structures clearly revealed the involvement of the H-bonding association of the two water molecules in fixing the orientation of the asparagine residue of the catalytic triad. From this study, it is suggested that H-bonding of the water molecule at the W1 invariant site better stabilizes the Asn residue at the active site of the catalytic triad.     

Characterization and partial purification of <Emphasis Type="Italic">Candida albicans</Emphasis> Secretory IL-12 Inhibitory Factor

Background  

We have previously shown that supernatant from Candida albicans (CA) culture contains a Secretory Interleukin (IL)-12 Inhibitory Factor (CA-SIIF), which inhibits IL-12 production by human monocytes. However, the effect of CA-SIIF on secretion of other cytokines by monocytes is unknown, and detailed characterization of this factor has not been performed.     

<Superscript>15</Superscript>N natural abundance of fossil peat reflects the influence of animal-derived nitrogen on vegetation

'¹⁵N signatures of fossil peat were used to interpret past ecosystem processes on tectonically active subantarctic Macquarie Island. By comparing past vegetation reconstructed from the fossil record with present-day vegetation analogues, our evidence strongly suggests that changes in the '¹⁵N signatures of fossil peat at this location reflect mainly past changes in the proportion of plant nitrogen derived from animal sources. Associated with uplift above sea level over the past 8,500 years, fossil records in two peat deposits on the island chronicle a change from coastal vegetation with fur and elephant seal disturbance to the existing inland herbfield. Coupled with this change are synchronous changes in the '¹⁵N signatures of peat layers. At two sites ¹⁵N-enriched peat '¹⁵N signatures of up to +17‰ were associated with a high abundance of pollen of the nitrophile Callitriche antarctica (Callitrichaceae). At one site fossil seal hair was also associated with enriched peat '¹⁵N. Less ¹⁵N enriched '¹⁵N signatures (e.g. -1.9‰ to +3.9‰) were measured in peat layers which lacked animal associated C. antarctica and Acaena spp. Interpretation of a third peat profile indicates continual occupation of a ridge site by burrowing petrels for most of the Holocene. We suggest that ¹⁵N signatures of fossil peat remained relatively stable with time once deposited, providing a significant new tool for interpreting the palaeoecology.     

Simulation methods with extended stability for stiff biochemical Kinetics

Background  

With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows.     

Typing of Genetic Markers Involved in Stress Response by Fluorescent cDNA-Amplified Fragment Length Polymorphism Technique

Identification of genetic markers involved in stress response to physical factors or chemical substances in organisms is a challenging task. Typing of upregulated gene expression due to selective antibacterial pressure is a promising approach in the search of molecular mechanisms responsible for development of resistance. cDNA-Fluorescent Amplified Fragment Length Polymorphism (cDNA-FAFLP) strategy was developed and applied in the search of antimycotic drug resistance marker(s) in medically important fungi as an alternative method to microarray analysis. We compared differential gene expression of two sensitive Candida albicans reference strains (ATCC 10231 and ATCC 60133) and two of their paired resistant to fluconazole and itraconazole mutants. Resistant mutants Candida albicans FLC-R, resistant to fluconazole (MIC > 128 μg/ml) and Candida albicans ICZ-R, resistant to itraconazole (MIC > 4 μg/ml) were obtained in subcultures with gradual increase of the antifungal in the culture medium. cDNA-AFLP profile in both itraconazole resistant mutants showed specific spectrophotometric peaks with 5–6-fold RNA overexpression product of 500 bp length compared to the sensitive strains. Fluconazole mutants do not reveal RNA level changes under tested by us typing conditions. These results indicate that the cDNA-FAFLP strategy is a relatively rapid, simple, and reliable method for simultaneous typing of both constitutive and induced differences in expression of host genes providing insight into the biological processes involved in response to drugs in bacteria and fungi. Moreover, this methodology could be tested for typing of the genome response of any organism to physical or chemical stress factors.