Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

Resolving response, decision, and strategic control: evidence for a functional topography in dorsomedial prefrontal cortex.

The dorsomedial prefrontal cortex (DMPFC) plays a central role in aspects of cognitive control and decision making. Here, we provide evidence for an anterior-to-posterior topography within the DMPFC using tasks that evoke three distinct forms of control demands--response, decision, and strategic--each of which could be mapped onto independent behavioral data. Specifically, we identify three spatially distinct regions within the DMPFC: a posterior region associated with control demands evoked by multiple incompatible responses, a middle region associated with control demands evoked by the relative desirability of decision options, and an anterior region that predicts control demands related to deviations from an individual's preferred decision-making strategy. These results provide new insight into the functional organization of DMPFC and suggest how recent controversies about its role in complex decision making and response mapping can be reconciled.

Mainland size variation informs predictive models of exceptional insular body size change in rodents.

The tendency for island populations of mammalian taxa to diverge in body size from their mainland counterparts consistently in particular directions is both impressive for its regularity and, especially among rodents, troublesome for its exceptions. However, previous studies have largely ignored mainland body size variation, treating size differences of any magnitude as equally noteworthy. Here, we use distributions of mainland population body sizes to identify island populations as 'extremely' big or small, and we compare traits of extreme populations and their islands with those of island populations more typical in body size. We find that although insular rodents vary in the directions of body size change, 'extreme' populations tend towards gigantism. With classification tree methods, we develop a predictive model, which points to resource limitations as major drivers in the few cases of insular dwarfism. Highly successful in classifying our dataset, our model also successfully predicts change in untested cases.

Predictive Modeling of Loss-of-Heterozygosity Events in Yeast

During mitotic cell cycles, DNA experiences many types of endogenous and exogenous damaging agents that could potentially cause double strand breaks (DSB). In S. cerevisiae, DSBs are primarily repaired by mitotic recombination and as a result, could lead to loss-of-heterozygosity (LOH). Genetic recombination can happen in both meiosis and mitosis. While genome-wide distribution of meiotic recombination events has been intensively studied, mitotic recombination events have not been mapped unbiasedly throughout the genome until recently. Methods for selecting mitotic crossovers and mapping the positions of crossovers have recently been developed in our lab. Our current approach uses a diploid yeast strain that is heterozygous for about 55,000 SNPs, and employs SNP-Microarrays to map LOH events throughout the genome. These methods allow us to examine selected crossovers and unselected mitotic recombination events (crossover, noncrossover and BIR) at about 1 kb resolution across the genome. Using this method, we generated maps of spontaneous and UV-induced LOH events. In this study, we explore machine learning and variable selection techniques to build a predictive model for where the LOH events occur in the genome.

Randomly from the yeast genome, we simulated control tracts resembling the LOH tracts in terms of tract lengths and locations with respect to single-nucleotide-polymorphism positions. We then extracted roughly 1,100 features such as base compositions, histone modifications, presence of tandem repeats etc. and train classifiers to distinguish control tracts and LOH tracts. We found interesting features of good predictive values. We also found that with the current repertoire of features, the prediction is generally better for spontaneous LOH events than UV-induced LOH events.

Genetic Variants of the MDM2 Gene Are Predictive of Treatment-Related Toxicities and Overall Survival in Patients With Advanced NSCLC.

INTRODUCTION: Platinum agents can cause the formation of DNA adducts and induce apoptosis to eliminate tumor cells. The aim of the present study was to investigate the influence of genetic variants of MDM2 on chemotherapy-related toxicities and clinical outcomes in patients with advanced non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: We recruited 663 patients with advanced NSCLC who had been treated with first-line platinum-based chemotherapy. Five tagging single nucleotide polymorphisms (SNPs) in MDM2 were genotyped in these patients. The associations of these SNPs with clinical toxicities and outcomes were evaluated using logistic regression and Cox regression analyses. RESULTS: Two SNPs (rs1470383 and rs1690924) showed significant associations with chemotherapy-related toxicities (ie, overall, hematologic, and gastrointestinal toxicity). Compared with the wild genotype AA carriers, patients with the GG genotype of rs1470383 had an increased risk of overall toxicity (odds ratio [OR], 3.28; 95% confidence interval [CI], 1.34-8.02; P = .009) and hematologic toxicity (OR, 4.10; 95% CI, 1.73-9.71; P = .001). Likewise, patients with the AG genotype of rs1690924 showed more sensitivity to gastrointestinal toxicity than did those with the wild-type homozygote GG (OR, 2.32; 95% CI, 1.30-4.14; P = .004). Stratified survival analysis revealed significant associations between rs1470383 genotypes and overall survival in patients without overall or hematologic toxicity (P = .007 and P = .0009, respectively). CONCLUSION: The results of our study suggest that SNPs in MDM2 might be used to predict the toxicities of platinum-based chemotherapy and overall survival in patients with advanced NSCLC. Additional validations of the association are warranted.

Neural network evidence for the coupling of presaccadic visual remapping to predictive eye position updating

As we look around a scene, we perceive it as continuous and stable even though each saccadic eye movement changes the visual input to the retinas. How the brain achieves this perceptual stabilization is unknown, but a major hypothesis is that it relies on presaccadic remapping, a process in which neurons shift their visual sensitivity to a new location in the scene just before each saccade. This hypothesis is difficult to test in vivo because complete, selective inactivation of remapping is currently intractable. We tested it in silico with a hierarchical, sheet-based neural network model of the visual and oculomotor system. The model generated saccadic commands to move a video camera abruptly. Visual input from the camera and internal copies of the saccadic movement commands, or corollary discharge, converged at a map-level simulation of the frontal eye field (FEF), a primate brain area known to receive such inputs. FEF output was combined with eye position signals to yield a suitable coordinate frame for guiding arm movements of a robot. Our operational definition of perceptual stability was "useful stability,” quantified as continuously accurate pointing to a visual object despite camera saccades. During training, the emergence of useful stability was correlated tightly with the emergence of presaccadic remapping in the FEF. Remapping depended on corollary discharge but its timing was synchronized to the updating of eye position. When coupled to predictive eye position signals, remapping served to stabilize the target representation for continuously accurate pointing. Graded inactivations of pathways in the model replicated, and helped to interpret, previous in vivo experiments. The results support the hypothesis that visual stability requires presaccadic remapping, provide explanations for the function and timing of remapping, and offer testable hypotheses for in vivo studies. We conclude that remapping allows for seamless coordinate frame transformations and quick actions despite visual afferent lags. With visual remapping in place for behavior, it may be exploited for perceptual continuity.