Characterization of Vesicular Monoamine Transporter 2 and its role in Parkinson\u27s Disease Pathogenesis using Drosophila

Parkinson’s disease (PD) is a progressive neurodegenerative disorder caused by the selective loss of the dopaminergic neurons in the Substantia nigra pars compacta region of the brain. PD is also the most common neurodegenerative disorder and the second most common movement disorder. PD patients exhibit the cardinal symptoms, including tremor of the extremities, rigidity, slowness of movement, and postural instability, after 70-80% of DA neurons degenerate. It is, therefore, imperative to elucidate the underlying mechanisms involved in the selective degeneration of DA neurons. Although increasing numbers of PD genes have been identified, why these largely widely expressed genes induce selective loss of DA neurons is still not known. Notably, dopamine (DA) itself is a chemically labile molecule and can become oxidized to toxic by-products while induce the accumulation of harmful molecules such as Reactive Oxygen Species (ROS). Accordingly, DA toxicity has long been suspected to play a role in selective neuronal loss in PD. Vesicular Monoamine Transporter (VMAT) is essential for proper vesicular storage of monoamines such as DA and their regulated release. Increasing evidence have linked VMAT dysfunction with Parkinson’s disease. In this study, we re-examine the gain- and loss-of-function phenotypes of the sole VMAT homologue in Drosophila. Our results suggest that the C-terminal sequences in the two encoded VMAT isoforms not only determine their differential subcellular localizations, but also their activities in content release. In particular, VMAT2 orthologue potentially poses a unique, previously unexplored activity in promoting DA release. On the other hand, by examining DA distribution in wildtype and VMAT mutant animals, we find that there exists intrinsic difference in the dynamics of intracellular DA handling among DA neurons clustered in different brain regions. Furthermore, loss of VMAT causes severe loss of total DA levels and a redistribution of DA in Drosophila brain. Lastly, removal of both VMAT and another PD gene parkin, which is also conserved in Drosophila, results in the selective loss of DA neurons, primarily in the protocerebral anterior medial (PAM) clusters of the brain. Our results suggest a potential involvement of cytoplasmic DA in selective degeneration of DA neurons and also implicating a role for a differential intracellular DA handling mechanism underlying the regional specificity of neuronal loss in PD patients

Socio-economic Profiles of Nutrition Label Users

This paper aims to explore the socio-economic profiles of the nutrition label users and focuses on seven key nutrients: calories, calories from fat, total fat, trans fat, saturated fat, cholesterol, and sodium. The data are from National Health and Nutrition Examination Survey (NHANES) 2005-2006 and Continuing Survey of Food Intakes by Individuals (CSFII) 1994-96. Similar conclusions are drawn from both data sets: those consumers who are older, better educated, higher income, female, and have higher nutrition knowledge will have higher probability to use nutrition labels; those consumers who are in larger size families and being either Hispanic or black have lower probability of using nutrition labels.Socio-economic, Profiles, Nutrition Label, Users, Agricultural and Food Policy, Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Marketing,

Artificial-Noise-Aided Secure Multi-Antenna Transmission with Limited Feedback

We present an optimized secure multi-antenna transmission approach based on artificial-noise-aided beamforming, with limited feedback from a desired single-antenna receiver. To deal with beamformer quantization errors as well as unknown eavesdropper channel characteristics, our approach is aimed at maximizing throughput under dual performance constraints - a connection outage constraint on the desired communication channel and a secrecy outage constraint to guard against eavesdropping. We propose an adaptive transmission strategy that judiciously selects the wiretap coding parameters, as well as the power allocation between the artificial noise and the information signal. This optimized solution reveals several important differences with respect to solutions designed previously under the assumption of perfect feedback. We also investigate the problem of how to most efficiently utilize the feedback bits. The simulation results indicate that a good design strategy is to use approximately 20% of these bits to quantize the channel gain information, with the remainder to quantize the channel direction, and this allocation is largely insensitive to the secrecy outage constraint imposed. In addition, we find that 8 feedback bits per transmit antenna is sufficient to achieve approximately 90% of the throughput attainable with perfect feedback.Comment: to appear in IEEE Transactions on Wireless Communication

Inverse design of disordered stealthy hyperuniform spin chains

Positioned between crystalline solids and liquids, disordered many-particle systems which are stealthy and hyperuniform represent new states of matter that are endowed with novel physical and thermodynamic properties. Such stealthy and hyperuniform states are unique in that they are transparent to radiation for a range of wavenumbers around the origin. In this work, we employ recently developed inverse statistical-mechanical methods, which seek to obtain the optimal set of interactions that will spontaneously produce a targeted structure or configuration as a unique ground state, to investigate the spin-spin interaction potentials required to stabilize disordered stealthy hyperuniform one-dimensional (1D) Ising-like spin chains. By performing an exhaustive search over the spin configurations that can be enumerated on periodic 1D integer lattices containing $N=2,3,\ldots,36$ sites, we were able to identify and structurally characterize \textit{all} stealthy hyperuniform spin chains in this range of system sizes. Within this pool of stealthy hyperuniform spin configurations, we then utilized such inverse optimization techniques to demonstrate that stealthy hyperuniform spin chains can be realized as either unique or degenerate disordered ground states of radial long-ranged (relative to the spin chain length) spin-spin interactions. Such exotic ground states are distinctly different from spin glasses in both their inherent structural properties and the nature of the spin-spin interactions required to stabilize them. As such, the implications and significance of the existence of such disordered stealthy hyperuniform ground state spin systems warrants further study, including whether their bulk physical properties and excited states, like their many-particle system counterparts, are singularly remarkable, and can be experimentally realized.Comment: 11 pages, 9 figure

Evaluation of selected CMIP6 models' simulation on Arctic sea ice

To evaluate whether CMIP6 models provide good simulation in Arctic sea-ice extent, thickness, and motion, selected 6 CMIP6 models are EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, GFDL-ESM4, MPI-ESM1-2-HR, NORESM2-LM. For CMIP6 models and observations, seasonal cycle and the annual variation from 1979-2014 of sea-ice extent were studied, for sea-ice thickness and sea-ice motion, the Arctic is separated into three regions, geographical distribution, inter-annual variation from 1979-2014, seasonal cycle, and trend were studied. Then student t-test is used to evaluate whether the model output has a significant difference from observation, to select the best model(s). For sea-ice extent, EC-Earth3 is overestimating sea-ice extent, especially in winter, BCC-CSM2-MR model underestimates sea-ice extent, ACCESS-CM2, MPI-ESM1-2-HR, NorESM2-LM models perform the best. For sea-ice thickness, BCC-CSM2-MR underestimates sea-ice thickness, EC-Earth3, ACCESS-CM2, and NORESM2-LM models are overestimating sea-ice thickness. GFDL-ESM4 and MPI-ESM1-2-HR have the best performance at sea-ice thickness simulation. For sea-ice motion, the MPI-ESM1-2-HR model overestimates sea-ice drifting speed all year round, ACCESS-CM2 model tends to overestimate sea-ice drifting speed in summer for region1 and region2, in region3 ACCESS-CM2 model mostly overestimate sea-ice motion except winter months. NorESM2-LM model has the best performance overall, and ACCESS-CM2 has the second-best simulation for region1 and region2. EC-Earth3 also has a satisfactory simulation for sea-ice motion. Models and observation also agree on common results for sea-ice properties: Maximum sea-ice extent occurs in March, and minimum sea-ice extent occurs in September. There's a decreasing trend of sea-ice extent. The Central Arctic and Canadian Archipelago always have the thickest sea ice, followed by the East Siberian Sea, Laptev Sea, and Chukchi Sea, Beaufort Sea. East Greenland Sea, Barents Sea, Buffin Bay, and the Kara Sea always have the thinnest sea ice. There's a decreasing trend for sea-ice thickness according to models, sea-ice is thicker in the Chukchi Sea and the Beaufort Sea than in Laptev and East Siberian seas. Winter sea-ice thickness is higher than in summer, and sea-ice thickness has a more rapid decreasing rate in summer than in winter. Laptev and the East Siberian Sea have the most rapidly sea-ice thinning process. Sea-ice thickness has seasonal cycle that maximum usually occurs in May, and minimum sea-ice thickness happens in October. For sea-ice motion, there's an increasing trend of sea-ice motion, and summer sea-ice motion has faster sea-ice motion than winter, Chukchi Sea, and the Beaufort Sea has faster sea-ice motion than Laptev and the East Siberian Sea. Corresponding with the comparatively faster-thinning in the Laptev and the East Siberian Seas simulated by models, there's also a faster increasing rate in the Laptev and the East Siberian Sea