A nucleotide binding rectification Brownian ratchet model for translocation of Y-family DNA polymerases

Y-family DNA polymerases are characterized by low-fidelity synthesis on undamaged DNA and ability to catalyze translesion synthesis over the damaged DNA. Their translocation along the DNA template is an important event during processive DNA synthesis. In this work we present a Brownian ratchet model for this translocation, where the directed translocation is rectified by the nucleotide binding to the polymerase. Using the model, different features of the available structures for Dpo4, Dbh and polymerase ι in binary and ternary forms can be easily explained. Other dynamic properties of the Y-family polymerases such as the fast translocation event upon dNTP binding for Dpo4 and the considerable variations of the processivity among the polymerases can also be well explained by using the model. In addition, some predicted results of the DNA synthesis rate versus the external force acting on Dpo4 and Dbh polymerases are presented. Moreover, we compare the effect of the external force on the DNA synthesis rate of the Y-family polymerase with that of the replicative DNA polymerase

Covert Tracking: A Combined ERP and Fixational Eye Movement Study

Attention can be directed to particular spatial locations, or to objects that appear at anticipated points in time. While most work has focused on spatial or temporal attention in isolation, we investigated covert tracking of smoothly moving objects, which requires continuous coordination of both. We tested two propositions about the neural and cognitive basis of this operation: first that covert tracking is a right hemisphere function, and second that pre-motor components of the oculomotor system are responsible for driving covert spatial attention during tracking. We simultaneously recorded event related potentials (ERPs) and eye position while participants covertly tracked dots that moved leftward or rightward at 12 or 20°/s. ERPs were sensitive to the direction of target motion. Topographic development in the leftward motion was a mirror image of the rightward motion, suggesting that both hemispheres contribute equally to covert tracking. Small shifts in eye position were also lateralized according to the direction of target motion, implying covert activation of the oculomotor system. The data addresses two outstanding questions about the nature of visuospatial tracking. First, covert tracking is reliant upon a symmetrical frontoparietal attentional system, rather than being right lateralized. Second, this same system controls both pursuit eye movements and covert tracking

Is analysing the nitrogen use at the plant canopy level a matter of choosing the right optimization criterion?

Optimization theory in combination with canopy modeling is potentially a powerful tool for evaluating the adaptive significance of photosynthesis-related plant traits. Yet its successful application has been hampered by a lack of agreement on the appropriate optimization criterion. Here we review how models based on different types of optimization criteria have been used to analyze traits—particularly N reallocation and leaf area indices—that determine photosynthetic nitrogen-use efficiency at the canopy level. By far the most commonly used approach is static-plant simple optimization (SSO). Static-plant simple optimization makes two assumptions: (1) plant traits are considered to be optimal when they maximize whole-stand daily photosynthesis, ignoring competitive interactions between individuals; (2) it assumes static plants, ignoring canopy dynamics (production and loss of leaves, and the reallocation and uptake of nitrogen) and the respiration of nonphotosynthetic tissue. Recent studies have addressed either the former problem through the application of evolutionary game theory (EGT) or the latter by applying dynamic-plant simple optimization (DSO), and have made considerable progress in our understanding of plant photosynthetic traits. However, we argue that future model studies should focus on combining these two approaches. We also point out that field observations can fit predictions from two models based on very different optimization criteria. In order to enhance our understanding of the adaptive significance of photosynthesis-related plant traits, there is thus an urgent need for experiments that test underlying optimization criteria and competing hypotheses about underlying mechanisms of optimization

Data from: Avoided heat-related mortality through climate adaptation in three US cities

Heat-related mortality in US cities is expected to more than double by the mid-to-late 21st century. Rising heat exposure in cities is projected to result from: 1) climate forcings from changing global atmospheric composition; and 2) local land surface characteristics responsible for the urban heat island effect. The extent to which heat management strategies designed to lessen the urban heat island effect could offset future heat-related mortality remains unexplored in the literature. Using coupled global and regional climate models with a human health effects model, we estimate changes in the number of heat-related deaths in 2050 resulting from modifications to vegetative cover and surface albedo across three climatically and demographically diverse US metropolitan areas: Atlanta, Georgia, Philadelphia, Pennsylvania, and Phoenix, Arizona. Employing separate health impact functions for average warm season and heat wave conditions in 2050, we find combinations of vegetation and albedo enhancement to offset projected increases in heat-related mortality by 40 to 99% across the three metropolitan regions. These results demonstrate the potential for extensive land surface changes in cities to provide adaptive benefits to urban populations at risk for rising heat exposure with climate change

WRF scenario output

WRF model output for each scenario, metropolitan area, and temperature metric combination

CULE_pop

2050 population projections for Atlanta, Philadelphia, and Phoeni