Metabolic control analysis as a strategy to identify therapeutic targets, the case of cancer glycolysis

The use of kinetic modeling and metabolic control analysis (MCA) to identify possible therapeutic targets and to investigate the controlling and regulatory mechanisms in cancer glycolysis is here reviewed. The glycolytic pathway has been considered a target to decrease cancer cell growth; however, its occurrence in normal cells makes it difficult to design therapeutic strategies that target this pathway in pathological cells. Notwithstanding, the over-expression of all enzymes and transporters, as well as the expression of isoenzymes with different kinetic and regulatory properties in cancer cells, suggested a different distribution of the control of glycolytic flux than that observed in normal cells. Kinetic models of glycolysis are constructed with enzyme kinetics experimental data, validated with the steady-state metabolite concentrations and glycolytic fluxes; applying MCA, permitted us to identify the steps with the highest control of glycolysis in cancer cells, but low control in normal cells. The cancer glycolysis main controlling steps under several metabolic conditions were: glucose transport, hexokinase and hexose-6-phosphate isomerase (HPI); whereas in normal cells were: the first two and phosphofructokinase-1. HPI is the best therapeutic target because it exerts high control in cancer glycolytic flux, but not in normal cells. Furthermore, kinetic modeling also contributed to identifying new feed-back and feed-forward regulatory loops in cancer cells glycolysis, and to understanding the mode of metabolic action of glycolytic inhibitors. Thus, MCA and metabolic modeling allowed to propose new strategies for inhibiting glycolysis in cancer cells.

Management strategy of the naked carp (Gymnocypris przewalskii) in the Qinghai lake using matrix population modeling

Naked carp (Gymnocypris przewalskii) is the only fish species commercially harvested in Qinghai Lake, which is the largest inland saltwater lake in China. Multiple ecological stresses such as long-term overfishing, drying-up of riverine inflows, and decreases in spawning habitat caused the naked carp population to decrease from 320,000 tons before the 1950s to only 3000 tons by the early 2000s. We used matrix projection population modeling to quantitatively simulate the dynamics of the naked carp population from the 1950s to the 2020s. Five versions of the matrix model were developed from the field and laboratory information that represented different population states (high but declining, low abundance, very low abundance, initial recovery, pristine). Equilibrium analysis was applied to density-independent versions of the matrices and population growth rate, age composition, and elasticities were compared among versions. Stochastic, density-dependent version of the most recent decade (recovering) version was used to simulate the time-dependent responses to a range of levels of artificial reproduction (addition of age-1 from hatchery) and of the pristine version to simulate combinations of fishing rate and minimum age of harvest. Results showed the major role of overfishing in the population decline and that the population growth rate was most sensitive to the survival of juveniles and the spawning success of early-age adults. Dynamic simulations showed a rapid population response to artificial reproduction when population abundance was low and that if artificial reproduction continues at its current level, then population biomass would reach 75% of its pristine biomass after 50 years. Simulations with the pristine version identified sustainable fishing levels and the importance of protecting the first few ages of maturity. Overall, modeling results showed that artificial reproduction under conditions of no fishing is an effective approach to restoring the naked carp population. Further effectiveness should consider maximizing survival in the months just after release and maintaining genetic and phenotypic diversity. More information on density-dependent growth, survival, and reproduction, as well as on the genetic diversity and growth and migratory behavior (phenotypic variation) of released and native-spawned fish, would help inform management and conservation strategies and practices going forward.

The relative impact of urbanization and precipitation on long-term water level variations in the Yangtze River Delta

The combined and individual hydrological impacts of climate variation and urbanization have been extensively discussed over the past few decades, yet little is known about the relative impact of each. In this paper we took one of the most developed regions worldwide, Yangtze River Delta, as an example to analyse the long-term relative impacts of precipitation and urbanization change on water level alterations, based on precipitation, water level series, and annual impervious area data from 1960 to 2015. Abrupt changes detection in the water level series divided the data into the pre-impact period (1960-1988) and impacted period (1989-2015), and relative impacts of precipitation and urbanization on the water level increase from pre-impacted to impacted period, as well as their spatial and seasonal variations were estimated with the elasticity method. The results indicated that the urbanization change showed no distinct influence on the water level rise in the pre-impact period, while the precipitation played distinct roles only during summer months in the impacted period; the precipitation dominated two thirds of the water level rise in flood season, and in non-flood season the urbanization controlled the two thirds of the water level rise; spatially, the water level variations in old and new urban area were dominated by precipitation and urbanization process respectively; compared with precipitation amount, the water level correlated more strongly to the contribution ratio of precipitation. The results would provide a good reference for flood control and water resource management in the river basin, especially in the economically developed areas.

The Importance of Reproduction for the Conservation of Slow-Growing Animal Populations

Both survival and reproduction are important fitness components, and thus critical to the viability of wildlife populations. Preventing one death (survival) or contributing one newborn (reproduction), has arguably the same effect on population dynamics-in each instance the population grows or is maintained by one additional member. However, for the conservation of slow-growing animal populations, the importance of reproduction is sometimes overlooked when evaluating wildlife management options. This has to do with the use of demographic sensitivity analyses, which quantify the relative contribution of vital rates to population growth. For slow-growing populations, the results of such analyses typically show that growth rates are more sensitive to changes in survival than to equal proportional changes in reproduction. Consequently, for slow-growing taxa, survival has been labelled a better fitness surrogate than reproduction. However, such a generalization, derived from conventional sensitivity analyses, is based on flawed approaches, such as omitting appropriate scaling of vital rates, and sometimes misinterpretations. In this chapter, I make the case that for the conservation of slow-growing species the role of reproduction is considerably greater than conventional sensitivity analyses would suggest. This is illustrated by case studies on wildlife populations that underscore the importance of reproduction for the conservation of slow-growing birds, ungulates, carnivores, and cetaceans.

The interacting effects of forestry and climate change on the demography of a group-living bird population

Anthropogenic degradation of natural habitats is a global driver of wildlife population declines. Local population responses to such environmental perturbations are generally well understood, but in socially structured populations, interactions between environmental and social factors may influence population responses. Thus, understanding how habitat degradation affects the dynamics of these populations requires simultaneous consideration of social and environmental mechanisms underlying demographic responses. Here we investigated the effect of habitat degradation through commercial forestry on spatiotemporal dynamics of a group-living bird, the Siberian jay, Perisoreus infaustus, in boreal forests of northern Sweden. We assessed the interacting effects of forestry, climate and population density on stage-specific, seasonal life-history rates and population dynamics, using long-term, individual-based demographic data from 70 territories in natural and managed forests. Stage-specific survival and reproductive rates, and consequently population growth, were lower in managed forests than in natural forests. Population growth was most sensitive to breeder survival and was more sensitive to early dispersing juveniles than those delaying dispersal. Forestry decreased population growth in managed forests by reducing reproductive success and breeder survival. Increased snow depth improved winter survival, and warmer spring temperatures enhanced reproductive success, particularly in natural forests. Population growth was stable in natural forests but it was declining in managed forests, and this difference accelerated under forecasted climate scenarios. Thus, climatic change could exacerbate the rate of forestry-induced population decline through reduced snow cover in our study species, and in other species with similar life-history characteristics and habitat requirements.

Exploring factors contributing to crash injury severity on rural two-lane highways

OBJECTIVE

Crash injury results from complex interaction among factors related to at-fault driver's behavior, vehicle characteristics, and road conditions. Identifying the significance of these factors which affect crash injury severity is critical for improving traffic safety. A method was developed to explore the relationship based on crash data collected on rural two-lane highways in China.

METHODS

There were 673 crash records collected on rural two-lane highways in China. A partial proportional odds model was developed to examine factors influencing crash injury severity owing to its high ability to accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of each contributing factor.

RESULTS

The results show that nine explanatory variables, including at-fault driver's age, at-fault driver having a license or not, alcohol usage, speeding, pedestrian involved, type of area, weather condition, pavement type, and collision type, significantly affect injury severity. In addition to alcohol usage and pedestrian involved, others violate the proportional odds assumption. At-fault driver's age of 25-39years, alcohol usage, speeding, pedestrian involved, pavement type of asphalt, and collision type of angle are found to be increased crash injury severity.

PRACTICAL APPLICATIONS

The developed logit model has demonstrated itself efficient in identifying the effect of contributing factors on the crash injury severity.

Analyzing the quality robustness of chemotherapy plans with respect to model uncertainties

Mathematical models of chemotherapy planning problems contain various biomedical parameters, whose values are difficult to quantify and thus subject to some uncertainty. This uncertainty propagates into the therapy plans computed on these models, which poses the question of robustness to the expected therapy quality. This work introduces a combined approach for analyzing the quality robustness of plans in terms of dosing levels with respect to model uncertainties in chemotherapy planning. It uses concepts from multi-criteria decision making for studying parameters related to the balancing between the different therapy goals, and concepts from sensitivity analysis for the examination of parameters describing the underlying biomedical processes and their interplay. This approach allows for a profound assessment of a therapy plan, how stable its quality is with respect to parametric changes in the used mathematical model.

Comparing plant life histories using elasticity analysis: the importance of life span and the number of life-cycle stages

Recent studies have used transition matrix elasticity analysis to investigate the relative role of survival (L), growth (G) and fecundity (F) in determining the estimated rate of population increase for perennial plants. The relative importance of these three variables has then been used as a framework for comparing patterns of plant life history in a triangular parameter space. Here we analyse the ways in which the number of life-cycle stages chosen to describe a species (transition matrix dimensionality) might influence the interpretation of such comparisons. Because transition matrix elements describing survival ("stasis") and growth are not independent, the number of stages used to describe a species influences their relative contribution to the population growth rate. Reduction in the number of stages increases the apparent importance of stasis relative to growth, since each becomes broader and fewer individuals make the transition to the next stage per unit time period. Analysis of a test matrix for a hypothetical tree species divided into 4-32 life-cycle stages confirms this. If the number of stages were defined in relation to species longevity so that mean residence time in each stage were approximately constant, then the elasticity of G would reflect the importance of relative growth rate to λ. An alternative, and simpler, approach to ensure comparability of results between species may be to use the same number of stages regardless of species longevity. Published studies for both herbaceous and woody species have tended to use relatively few stages to describe life cycles (herbs: n=45, [Formula: see text]; woody plants: n=21, [Formula: see text]) and so approximate this approach. By using the same number of stages regardless of longevities, the position of species along the G-L side of the triangular parameter space largely reflects differences in longevity. The extent of variation in elasticity for L, G and F within and between species may also be related to factors such as successional status and habitat. For example, the shade-tolerant woody species, Araucaria cunninghamii, shows greater importance for stasis (L), while the gap-phase congener species, Araucaria hunsteinii, shows higher values for G (although values are likely to vary with the stage of stand development).