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A model [Wachtershauser, G. (1988) Microbiol. Rev. 52, 452-484], according to which life started in the form of a monomolecular layer of interacting anionic metabolites electrostatically bound to a positively charged surface, is examined critically. The model raises a number of thermodynamic and kinetic difficulties.
Microbial activity in the Antarctic cryptoendolithic habitat is regulated primarily by temperature. Previous field studies have provided some information on the thermal regime in this habitat, but this type of information is limited by the remoteness of the site and the harsh climatic conditions. Therefore, a mathematical model of the endolithic thermal regime was constructed to augment the field data. This model enabled the parameters affecting the horizontal and altitudinal distribution of the community to be examined. The model predicts that colonization should be possible on surfaces with zenith angle less than 15 degrees. At greater zenith angles, colonization should be restricted to surfaces with azimuth angles less than 135 degrees or greater than 225 degrees. The upper elevational limit of the community should be less than 2,500 m. The thermal regime probably does not influence the zonation of the community within a rock.
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Understanding the systematic and quantitative correlation between the physical events of energy deposition by ionizing radiation and the ensuing chemical and biochemical processes leading to DNA damage is one of the goals in radiation research. Significant progress has been made toward achieving the stated goal by using theoretical modeling techniques. These techniques are strongly dependent on computer simulation procedures. A review of such techniques with details of various stages of simulation development, including a comparison with available experimental data, is presented in this article.
A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.
Phenological development affects canopy structure, radiation interception, and dry matter production; most crop simulation models therefore incorporate leaf emergence rate as a basic parameter. A recent study examined leaf emergence rate as a function of temperature and daylength among wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) cultivars. Leaf emergence rate and phyllochron were modeled as functions of temperature alone, daylength alone, and the interaction between temperature and daylength. The resulting equations contained an unwieldy number of constants. Here we simplify by reducing the constants by > 70%, and show leaf emergence rate as a single response surface with temperature and daylength. In addition, we incorporate the effect of photosynthetic photon flux into the model. Generic fits for wheat and barley show cultivar differences less than +/- 5% for wheat and less than +/- 10% for barley. Barley is more sensitive to daylength changes than wheat for common environmental values of daylength, which may be related to the difference in sensitivity to daylength between spring and winter cultivars. Differences in leaf emergence rate between cultivars can be incorporated into the model by means of a single, nondimensional factor for each cultivar.
The phylogeny and timescale of life are becoming better understood as the analysis of genomic data from model organisms continues to grow. As a result, discoveries are being made about the early history of life and the origin and development of complex multicellular life. This emerging comparative framework and the emphasis on historical patterns is helping to bridge barriers among organism-based research communities.
Mass transport and mixing of perfused scalar quantities in the NASA Rotating Wall Perfused Vessel bioreactor are studied using numerical models of the flow field and scalar concentration field. Operating conditions typical of both microgravity and ground-based cell cultures are studied to determine the expected vessel performance for both flight and ground-based control experiments. Results are presented for the transport of oxygen with cell densities and consumption rates typical of colon cancer cells cultured in the RWPV. The transport and mixing characteristics are first investigated with a step change in the perfusion inlet concentration by computing the time histories of the time to exceed 10% inlet concentration. The effects of a uniform cell utilization rate are then investigated with time histories of the outlet concentration, volume average concentration, and volume fraction starved. It is found that the operating conditions used in microgravity produce results that are quite different then those for ground-based conditions. Mixing times for microgravity conditions are significantly shorter than those for ground-based operation. Increasing the differential rotation rates (microgravity) increases the mixing and transport, while increasing the mean rotation rate (ground-based) suppresses both. Increasing perfusion rates enhances mass transport for both microgravity and ground-based cases, however, for the present range of operating conditions, above 5-10 cc/min there are diminishing returns as much of the inlet fluid is transported directly to the perfusion exit. The results show that exit concentration is not a good indicator of the concentration distributions in the vessel. In microgravity conditions, the NASA RWPV bioreactor with the viscous pump has been shown to provide an environment that is well mixed. Even when operated near the theoretical minimum perfusion rates, only a small fraction of the volume provides less than the required oxygen levels. 2002 Wiley Periodicals, Inc.
The present paper presents a thermodynamic approach to assess the quality of human-thermal environment interaction and quantify thermal comfort. The approach involves development of entropy generation term by applying second law of thermodynamics to the combined human-environment system. The entropy generation term combines both human thermal physiological responses and thermal environmental variables to provide an objective measure of thermal comfort. The original concepts and definitions form the basis for establishing the mathematical relationship between thermal comfort and entropy generation term. As a result of logic and deterministic approach, an Objective Thermal Comfort Index (OTCI) is defined and established as a function of entropy generation. In order to verify the entropy-based thermal comfort model, human thermal physiological responses due to changes in ambient conditions are simulated using a well established and validated human thermal model developed at the Institute of Environmental Research of Kansas State University (KSU). The finite element based KSU human thermal computer model is being utilized as a "Computational Environmental Chamber" to conduct series of simulations to examine the human thermal responses to different environmental conditions. The output from the simulation, which include human thermal responses and input data consisting of environmental conditions are fed into the thermal comfort model. Continuous monitoring of thermal comfort in comfortable and extreme environmental conditions is demonstrated. The Objective Thermal Comfort values obtained from the entropy-based model are validated against regression based Predicted Mean Vote (PMV) values. Using the corresponding air temperatures and vapor pressures that were used in the computer simulation in the regression equation generates the PMV values. The preliminary results indicate that the OTCI and PMV values correlate well under ideal conditions. However, an experimental study is needed in the future to fully establish the validity of the OTCI formula and the model. One of the practical applications of this index is that could it be integrated in thermal control systems to develop human-centered environmental control systems for potential use in aircraft, mass transit vehicles, intelligent building systems, and space vehicles.
Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.
By mapping nucleotide sequences onto a "DNA walk", we uncovered remarkably long-range power law correlations [Nature 356 (1992) 168] that imply a new scale invariant property of DNA. We found such long-range correlations in intron-containing genes and in non-transcribed regulatory DNA sequences, but not in cDNA sequences or intron-less genes. In this paper, we present more explicit evidences to support our findings.
The carbon isotope effects associated with synthesis of methane from acetate have been determined for Methanosarcina barkeri 227 and for methanogenic archaea in sediments of Wintergreen Lake, Michigan. At 37 degrees C, the 13C isotope effect for the reaction acetate (methyl carbon) --> methane, as measured in replicate experiments with M. barkeri, was - 21.3% +/- 0.3%. The isotope effect at the carboxyl portion of acetate was essentially equal, indicating participation of both positions in the rate-determining step, as expected for reactions catalyzed by carbon monoxide dehydrogenase. A similar isotope effect, - 19.2% +/- 0.3% was found for this reaction in the natural community (temperature = 20 degrees C). Given these observations, it has been possible to model the flow of carbon to methane within lake sediment communities and to account for carbon isotope compositions of evolving methane. Extension of the model allows interpretation of seasonal fluctuations in 13C contents of methane in other systems.
BACKGROUND: We have described the rapid destruction of young red blood cells (neocytolysis) in astronauts adapting to microgravity, in polycythemic high altitude dwellers who descend to sea level, and in patients with kidney disorders. This destruction results from a decrease in erythropoietin (EPO) production. We hypothesized that such EPO withdrawal could trigger physiological changes in cells other than red cell precursors and possibly lead to the uptake and destruction of young red cells by altering endothelial cell-macrophage interactions, most likely occurring in the spleen. METHODS: We identified EPO receptors on human splenic endothelial cells (HSEC) and investigated the responses of these cells to EPO withdrawal. RESULTS: A monolayer of HSEC, unlike human endothelial cells from aorta, glomerulus, or umbilical vein, demonstrated an increase in permeability upon EPO withdrawal that was accompanied by unique morphological changes. When HSEC were cultured with monocyte-derived macrophages (but not when either cell type was cultured alone), EPO withdrawal induced an increased ingestion of young red cells by macrophages when compared with the constant presence or absence of EPO. CONCLUSIONS: HSEC may represent a unique cell type that is able to respond to EPO withdrawal by increasing permeability and interacting with phagocytic macrophages, which leads to neocytolysis.
We extended the model of the ventricular myocyte by Winslow et al. (Circ. Res 1999, 84:571-586) by incorporating equations for Ca(2+) and Mg(2+) buffering and transport by ATP and ADP and equations for MgATP regulation of ion transporters (Na(+)-K(+) pump, sarcolemmal and sarcoplasmic Ca(2+) pumps). The results indicate that, under normal conditions, Ca(2+) binding by low-affinity ATP and diffusion of CaATP may affect the amplitude and time course of intracellular Ca(2+) signals. The model also suggests that a fall in ATP/ADP ratio significantly reduces sarcoplasmic Ca(2+) content, increases diastolic Ca(2+), lowers systolic Ca(2+), increases Ca(2+) influx through L-type channels, and decreases the efficiency of the Na(+)/Ca(2+) exchanger in extruding Ca(2+) during periodic voltage-clamp stimulation. The analysis suggests that the most important reason for these changes during metabolic inhibition is the down-regulation of the sarcoplasmic Ca(2+)-ATPase pump by reduced diastolic MgATP levels. High Ca(2+) concentrations developed near the membrane might have a greater influence on Mg(2+), ATP, and ADP concentrations than that of the lower Ca(2+) concentrations in the bulk myoplasm. The model predictions are in general agreement with experimental observations measured under normal and pathological conditions.
A major theme of the 1990s in the pathophysiology of nervous system injury has been the multifactorial etiology of irreversible injury. Multiple causes imply multiple opportunities for therapeutic intervention--hence the abandonment of the "magic bullet" single pharmacologic agent for neuroprotection in favor of pharmacologic "cocktails". A second theme of the 1990s has been the progress in technology for neuroprotection, minimally- or non-invasive monitoring as well as treatment. Cardiac stenting has eliminated the need, in many cases, for open heart surgery; deep brain stimulation for Parkinson's disease has offered significant improvement in quality of life for many who had exhausted cocktail drug treatment for their disease. Deep brain stimulation of the subthalamic nucleus offers a novel treatment for Parkinson's disease where a technological advance may actually be an intervention with effects that are normally expected from pharmacologic agents. Rather than merely "jamming" the nervous system circuits involved in Parkinson's disease, deep brain stimulation of the subthalamic nucleus appears to improve the neurotransmitter imbalance that lies at the heart of Parkinson's disease. It may also slow the progression of the disease. Given the example of deep brain stimulation of the subthalamic nucleus for Parkinson's disease, in future one may expect other technological or "hardware" interventions to influence the programming or "software" of the nervous system's physiologic response in certain disease states.
It is common in vestibular and oculomotor testing to use a single-frequency (sine) or combination of frequencies [sum-of-sines (SOS)] stimulus for head or target motion. The resulting eye movements typically contain a smooth tracking component, which follows the stimulus, in which are interspersed rapid eye movements (saccades or fast phases). The parameters of the smooth tracking--the amplitude and phase of each component frequency--are of interest; many methods have been devised that attempt to identify and remove the fast eye movements from the smooth. We describe a new approach to this problem, tailored to both single-frequency and sum-of-sines stimulation of the human linear vestibulo-ocular reflex. An approximate derivative is used to identify fast movements, which are then omitted from further analysis. The remaining points form a series of smooth tracking segments. A genetic algorithm is used to fit these segments together to form a smooth (but disconnected) wave form, by iteratively removing biases due to the missing fast phases. A genetic algorithm is an iterative optimization procedure; it provides a basis for extending this approach to more complex stimulus-response situations. In the SOS case, the genetic algorithm estimates the amplitude and phase values of the component frequencies as well as removing biases.
Scientific knowledge develops through the evolution of new concepts. This process is usually driven by new methodologies that provide observations not previously available. Understanding of pulmonary blood flow determinants advanced significantly in the 1960s and is now changing rapidly again, because of increased spatial resolution of regional pulmonary blood flow measurements.
The plasma concentration-time profiles following oral administration of drugs are often irregular and cannot be interpreted easily with conventional models based on first- or zero-order absorption kinetics and lag time. Six new models were developed using a time-dependent absorption rate coefficient, ka(t), wherein the time dependency was varied to account for the dynamic processes such as changes in fluid absorption or secretion, in absorption surface area, and in motility with time, in the gastrointestinal tract. In the present study, the plasma concentration profiles of propranolol obtained in human subjects following oral dosing were analyzed using the newly derived models based on mass balance and compared with the conventional models. Nonlinear regression analysis indicated that the conventional compartment model including lag time (CLAG model) could not predict the rapid initial increase in plasma concentration after dosing and the predicted Cmax values were much lower than that observed. On the other hand, all models with the time-dependent absorption rate coefficient, ka(t), were superior to the CLAG model in predicting plasma concentration profiles. Based on Akaike's Information Criterion (AIC), the fluid absorption model without lag time (FA model) exhibited the best overall fit to the data. The two-phase model including lag time, TPLAG model was also found to be a good model judging from the values of sum of squares. This model also described the irregular profiles of plasma concentration with time and frequently predicted Cmax values satisfactorily. A comparison of the absorption rate profiles also suggested that the TPLAG model is better at prediction of irregular absorption kinetics than the FA model. In conclusion, the incorporation of a time-dependent absorption rate coefficient ka(t) allows the prediction of nonlinear absorption characteristics in a more reliable manner.