HB12-1278 Study of the South Platte River alluvial aquifer

December 2013.Includes bibliographical references

Low-Intensity Exercise Induces Acute Shifts In Liver And Skeletal Muscle Substrate Metabolism But Not Chronic Adaptations In Tissue Oxidative Capacity

Adaptations in hepatic and skeletal muscle substrate metabolism following acute and chronic (6 wk; 5 days/wk; 1 h/day) low-intensity treadmill exercise were tested in healthy male C57BL/6J mice. Low-intensity exercise maximizes lipid utilization; therefore, we hypothesized pathways involved in lipid metabolism would be most robustly affected. Acute exercise nearly depleted liver glycogen immediately postexercise (0 h), whereas hepatic triglyceride (TAG) stores increased in the early stages after exercise (0-3 h). Also, hepatic peroxisome proliferator-activated receptor-gamma coactivator-1 alpha (PGC-1 alpha) gene expression and fat oxidation (mitochondrial and peroxisomal) increased immediately postexercise (0 h), whereas carbohydrate and amino acid oxidation in liver peaked 24-48 h later. Alternatively, skeletal muscle exhibited a less robust response to acute exercise as stored substrates (glycogen and TAG) remained unchanged, induction of PGC-1 alpha gene expression was delayed (up at 3 h), and mitochondrial substrate oxidation pathways (carbohydrate, amino acid, and lipid) were largely unaltered. Peroxisomal lipid oxidation exhibited the most dynamic changes in skeletal muscle substrate metabolism after acute exercise; however, this response was also delayed (peaked 3-24 h postexercise), and expression of peroxisomal genes remained unaffected. Interestingly, 6 wk of training at a similar intensity limited weight gain, increased muscle glycogen, and reduced TAG accrual in liver and muscle; however, substrate oxidation pathways remained unaltered in both tissues. Collectively, these results suggest changes in substrate metabolism induced by an acute low-intensity exercise bout in healthy mice are more rapid and robust in liver than in skeletal muscle; however, training at a similar intensity for 6 wk is insufficient to induce remodeling of substrate metabolism pathways in either tissue. NEW & NOTEWORTHY Effects of low-intensity exercise on substrate metabolism pathways were tested in liver and skeletal muscle of healthy mice. This is the first study to describe exercise-induced adaptations in peroxisomal lipid metabolism and also reports comprehensive adaptations in mitochondrial substrate metabolism pathways (carbohydrate, lipid, and amino acid). Acute low-intensity exercise induced shifts in mitochondrial and peroxisomal metabolism in both tissues, but training at this intensity did not induce adaptive remodeling of metabolic pathways in healthy mice

Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches

Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process-based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross-disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity

Neuromatch Academy: Teaching Computational Neuroscience with Global Accessibility

Neuromatch Academy (NMA) designed and ran a fully online 3-week Computational Neuroscience Summer School for 1757 students with 191 teaching assistants (TAs) working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility

Best practices in data analysis and sharing in neuroimaging using MRI

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping, and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world’s neuroimaging data

Failure of Working Memory Training to Enhance Cognition or Intelligence

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.National Institutes of Health (U.S.) (Blueprint for Neuroscience Research (T90DA022759/R90DA023427)United States. Defense Advanced Research Projects Agency (government contract no. NBCHC070105)United States. Dept. of Defense (National Defense Science and Engineering Fellowship)Massachusetts Institute of Technology (Sheldon Razin (1959) Fellowship

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%–94% of first‐order sensitivity index), industrial (7%–31%), and agricultural emissions (0%–24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%–81%, down to 15.3–25.9 μg m−3, remaining above the World Health Organization annual guideline of 10 μg m−3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m−3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors