Task-Dependent Differences in Operant Behaviors of Rats With Acute Exposure to High Ambient Temperature: A Potential Role of Hippocampal Dopamine Reuptake Transporters

Behavioral or cognitive functions are known to be influenced by thermal stress from the change in ambient temperature (Ta). However, little is known about how increased Ta (i.e., when the weather becomes warm or hot) may affect operant conditioned behavior and the neural substrates involved. The present study thus investigated the effects of high Ta on operant behaviors maintained on a fixed-ratio 1 (FR1) and a differential reinforcement for low-rate responding 10 s (DRL 10-s) schedule of reinforcement. The rats were randomly assigned to three groups receiving acute exposure to Ta of 23°C, 28°C, and 35°C, respectively, for evaluating the effects of high Ta exposure on four behavioral tests. Behavioral responses in an elevated T-maze and locomotor activity were not affected by Ta treatment. Regarding operant tests, while the total responses of FR1 behavior were decreased only under 35°C when compared with the control group of 23°C, those of DRL 10-s behavior were significantly reduced in both groups of 28°C and 35°C. Distinct patterns of inter-response time (IRT) distribution of DRL behavior appeared among the three groups; between-group differences of behavioral changes produced by high Ta exposure were confirmed by quantitative analyses of IRT data. Western blot assays of dopamine (DA) D1 and D2 receptor, DA transporter (DAT) and brain-derived neurotrophic factor (BDNF) were conducted for the sample tissues collected in six brain areas from all the subjects after acute high Ta exposure. Significant Ta-related effects were only revealed in the dorsal hippocampus (dHIP). In which, the DAT levels were increased in a Ta-dependent fashion that was associated with operant behavior changes under high Ta exposure. And, there as an increased level of D1 receptors in the 28°C group. In summary, these data indicate that the performance of operant behavior affected by the present high Ta exposure is task-dependent, and these changes of operant behaviors cannot be attributed to gross motor function or anxiety being affected. The regulation of dHIP DAT may be involved in this operant behavioral change under high Ta exposure

Emerged HA and NA Mutants of the Pandemic Influenza H1N1 Viruses with Increasing Epidemiological Significance in Taipei and Kaohsiung, Taiwan, 2009–10

The 2009 influenza pandemic provided an opportunity to observe dynamic changes of the hemagglutinin (HA) and neuraminidase (NA) of pH1N1 strains that spread in two metropolitan areas -Taipei and Kaohsiung. We observed cumulative increases of amino acid substitutions of both HA and NA that were higher in the post–peak than in the pre-peak period of the epidemic. About 14.94% and 3.44% of 174 isolates had one and two amino acids changes, respective, in the four antigenic sites. One unique adaptive mutation of HA2 (E374K) was first detected three weeks before the epidemic peak. This mutation evolved through the epidemic, and finally emerged as the major circulated strain, with significantly higher frequency in the post-peak period than in the pre-peak (64.65% vs 9.28%, p<0.0001). E374K persisted until ten months post-nationwide vaccination without further antigenic changes (e.g. prior to the highest selective pressure). In public health measures, the epidemic peaked at seven weeks after oseltamivir treatment was initiated. The emerging E374K mutants spread before the first peak of school class suspension, extended their survival in high-density population areas before vaccination, dominated in the second wave of class suspension, and were fixed as herd immunity developed. The tempo-spatial spreading of E374K mutants was more concentrated during the post–peak (p = 0.000004) in seven districts with higher spatial clusters (p<0.001). This is the first study examining viral changes during the naïve phase of a pandemic of influenza through integrated virological/serological/clinical surveillance, tempo-spatial analysis, and intervention policies. The vaccination increased the percentage of E374K mutants (22.86% vs 72.34%, p<0.001) and significantly elevated the frequency of mutations in Sa antigenic site (2.36% vs 23.40%, p<0.001). Future pre-vaccination public health efforts should monitor amino acids of HA and NA of pandemic influenza viruses isolated at exponential and peak phases in areas with high cluster cases

An Overview of Regional Experiments on Biomass Burning Aerosols and Related Pollutants in Southeast Asia: From BASE-ASIA and the Dongsha Experiment to 7-SEAS

By modulating the Earth-atmosphere energy, hydrological and biogeochemical cycles, and affecting regional-to-global weather and climate, biomass burning is recognized as one of the major factors affecting the global carbon cycle. However, few comprehensive and wide-ranging experiments have been conducted to characterize biomass-burning pollutants in Southeast Asia (SEA) or assess their regional impact on meteorology, the hydrological cycle, the radiative budget, or climate change. Recently, BASEASIA (Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment) and the 7-SEAS (7- South-East Asian Studies) Dongsha Experiment were conducted during the spring seasons of 2006 and 2010 in northern SEA, respectively, to characterize the chemical, physical, and radiative properties of biomass-burning emissions near the source regions, and assess their effects. This paper provides an overview of results from these two campaigns and related studies collected in this special issue, entitled Observation, modeling and impact studies of biomass burning and pollution in the SE Asian Environment. This volume includes 28 papers, which provide a synopsis of the experiments, regional weatherclimate, chemical characterization of biomass-burning aerosols and related pollutants in source and sink regions, the spatial distribution of air toxics (atmospheric mercury and dioxins) in source and remote areas, a characterization of aerosol physical, optical, and radiative properties, as well as modeling and impact studies. These studies, taken together, provide the first relatively complete dataset of aerosol chemistry and physical observations conducted in the sourcesink region in the northern SEA, with particular emphasis on the marine boundary layer and lower free troposphere (LFT). The data, analysis and modeling included in these papers advance our present knowledge of source characterization of biomass-burning pollutants near the source regions as well as the physical and chemical processes along transport pathways. In addition, we raise key questions to be addressed by a coming deployment during springtime 2013 in northern SEA, named 7-SEASBASELInE (Biomass-burning Aerosols Stratocumulus Environment: Lifecycles and Interactions Experiment). This campaign will include a synergistic approach for further exploring many key atmospheric processes (e.g., complex aerosol-cloud interactions) and impacts of biomass burning on the surface-atmosphere energy budgets during the lifecycles of biomass burning emissions

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Modified base-stock policies for semiconductor production system with dependent yield rates

We consider a two-stage production system faced by semiconductor manufacturing which produces a hierarchy of multiple grades of outputs. In the first stage, a single type of input (wafer) is used to produce multiple types of semi-finished parts with dependent yield rates, and in the second stage, each type of semi-finished parts can be transformed into a corresponding type of final products, or downgraded to a type of lower grade final products. Random customer demands are faced on the final products, and demands of different types of final products are not allowed to be substituted. The advantage of this production system is that it can prevent unhealthy ordering from customers who intentionally send out false demand signals for high grade products and revise the orders to lower grade products when the delivery time is close, which was observed in semiconductor manufacturing. The objective of the study is to plan the quantity of the input at the first stage and the respective downgrade quantities at the second stage so as to meet the required service level at the minimum cost. With some common assumptions, we propose a modified base-stock policy for this two-stage production system and show that the occurrence of nil excess inventory above the base-stock level follows a renewal process. We further extend the modified base-stock policy to a better policy that invokes risk pooling over multiple grade products. The performance of these two polices are evaluated via simulation to provide managerial insights.Semiconductor production system Modified base-stock policy Yield rates

Abstract Decision Tree Pruning via Integer Programming ⋆

Decision tree is an important tool for classification in data mining. Many algorithms have been proposed to induce decision trees and most of them involve two phases, a growing phase and a pruning phase. In this paper, we concentrate on the pruning problem. We find that with the ultimate aim of selecting the best sub-tree with the minimal error for a separate test set, the problem can be formulated as an integer program with a nice structure. By exploiting the special structure of this integer program, we propose several interesting algorithms to identify the optimal sub-tree, including the one that is essentially the same as the well-known bottom-up pruning method with computational complexity of O(n). A new optimality proof of the above algorithm is provided from the perspective of mathematical programming