The Empirical Analysis of Cigarette Tax Avoidance and Illicit Trade in Vietnam, 1998-2010

Illicit trade carries the potential to magnify existing tobacco-related health care costs through increased availability of untaxed and inexpensive cigarettes. What is known with respect to the magnitude of illicit trade for Vietnam is produced primarily by the industry, and methodologies are typically opaque. Independent assessment of the illicit cigarette trade in Vietnam is vital to tobacco control policy. This paper measures the magnitude of illicit cigarette trade for Vietnam between 1998 and 2010 using two methods, discrepancies between legitimate domestic cigarette sales and domestic tobacco consumption estimated from surveys, and trade discrepancies as recorded by Vietnam and trade partners. The results indicate that Vietnam likely experienced net smuggling in during the period studied. With the inclusion of adjustments for survey respondent under-reporting, inward illicit trade likely occurred in three of the four years for which surveys were available. Discrepancies in trade records indicate that the value of smuggled cigarettes into Vietnam ranges from $100 million to $300 million between 2000 and 2010 and that these cigarettes primarily originate in Singapore, Hong Kong, Macao, Malaysia, and Australia. Notable differences in trends over time exist between the two methods, but by comparison, the industry estimates consistently place the magnitude of illicit trade at the upper bounds of what this study shows. The unavailability of annual, survey-based estimates of consumption may obscure the true, annual trend over time. Second, as surveys changed over time, estimates relying on them may be inconsistent with one another. Finally, these two methods measure different components of illicit trade, specifically consumption of illicit cigarettes regardless of origin and smuggling of cigarettes into a particular market. However, absent a gold standard, comparisons of different approaches to illicit trade measurement serve efforts to refine and improve measurement approaches and estimates.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Genetic and evolutionary relationships among Asian Macaques

Published gene frequency data, checked for consistency of allele definitions across laboratories and for comparability of geographically identical samples, were pooled into a data set containing frequencies at nine loci for each of 20 populations that encompassed 10 macaque species. Genetic distances were calculated by the methods of Kidd and Cavalli-Sforza (1974). These distances were used to construct phylogenetic trees and to evaluate the relationships between divergence times and effective population sizes. Inter-and intraspecific genetic distances and the groupings defined by phenetic tree analyses support Fooden’s (1976) classification of the genus Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain Macacainto four species groups. A paleozoogeographical model of Asia including the known times of major sea-level changes allows us to explain qualitatively the inferred evolutionary relationships among macaque species. Many assumptions are required in order to estimate the variables necessary in the quantitative prediction of genetic differences for a comparison between any two populations. Examination of those assumptions demonstrates the need for more accurate genetic as well as paleozoogeographic information. An erratum to this article is available at .     

‘Mild mitochondrial uncoupling’ induced protection against neuronal excitotoxicity requires AMPK activity

The preconditioning response conferred by a mild uncoupling of the mitochondrial membrane potential (Δψ_m) has been attributed to altered reactive oxygen species (ROS) production and mitochondrial Ca^2 + uptake within the cells. Here we have explored if altered cellular energetics in response to a mild mitochondrial uncoupling stimulus may also contribute to the protection. The addition of 100 nM FCCP for 30 min to cerebellar granule neurons (CGNs) induced a transient depolarization of the Δψ_m, that was sufficient to significantly reduce CGN vulnerability to the excitotoxic stimulus, glutamate. On investigation, the mild mitochondrial ‘uncoupling’ stimulus resulted in a significant increase in the plasma membrane levels of the glucose transporter isoform 3, with a hyperpolarisation of Δψ_m and increased cellular ATP levels also evident following the washout of FCCP. Furthermore, the phosphorylation state of AMP-activated protein kinase (AMPK) (Thr 172) was increased within 5 min of the uncoupling stimulus and elevated up to 1 h after washout. Significantly, the physiological changes and protection evident after the mild uncoupling stimulus were lost in CGNs when AMPK activity was inhibited. This study identifies an additional mechanism through which protection is mediated upon mild mitochondrial uncoupling: it implicates increased AMPK signalling and an adaptive shift in energy metabolism as mediators of the preconditioning response associated with FCCP-induced mild mitochondrial uncoupling.     

Neto2 Interacts with the Scaffolding Protein GRIP and Regulates Synaptic Abundance of Kainate Receptors

Kainate receptors (KARs) are a class of ionotropic glutamate receptors that are expressed throughout the central nervous system. The function and subcellular localization of KARs are tightly regulated by accessory proteins. We have previously identified the single-pass transmembrane proteins, Neto1 and Neto2, to be associated with native KARs. In the hippocampus, Neto1, but not Neto2, controls the abundance and modulates the kinetics of postsynaptic KARs. Here we evaluated whether Neto2 regulates synaptic KAR levels in the cerebellum where Neto1 expression is limited to the deep cerebellar nuclei. In the cerebellum, where Neto2 is present abundantly, we found a ∼40% decrease in GluK2-KARs at the postsynaptic density (PSD) of Neto2-null mice. No change, however, was observed in total level of GluK2-KARs, thereby suggesting a critical role of Neto2 on the synaptic localization of cerebellar KARs. The presence of a putative class II PDZ binding motif on Neto2 led us to also investigate whether it interacts with PDZ domain-containing proteins previously implicated in regulating synaptic abundance of KARs. We identified a PDZ-dependent interaction between Neto2 and the scaffolding protein GRIP. Furthermore, coexpression of Neto2 significantly increased the amount of GRIP associated with GluK2, suggesting that Neto2 may promote and/or stabilize GluK2:GRIP interactions. Our results demonstrate that Neto2, like Neto1, is an important auxiliary protein for modulating the synaptic levels of KARs. Moreover, we propose that the interactions of Neto1/2 with various scaffolding proteins is a critical mechanism by which KARs are stabilized at diverse synapses.     

Automated extraction of bank angles from bird‐borne video footage using open‐source software

The use of miniaturized video cameras to study the at‐sea behavior of flying seabirds has increased in recent years. These cameras allow researchers to record several behaviors that were not previously possible to observe. However, video recorders produce large amounts of data and videos can often be time‐consuming to analyze. We present a new technique using open‐source software to extract bank angles from bird‐borne video footage. Bank angle is a key facet of dynamic soaring, which allows albatrosses and petrels to efficiently search vast areas of ocean for food. Miniaturized video cameras were deployed on 28 Wandering Albatrosses (Diomedea exulans) on Marion Island (one of the two Prince Edward Islands) from 2016 to 2018. The OpenCV library for the Python programming language was used to extract the angle of the horizon relative to the bird’s body (= bank angle) from footage when the birds were flying using a series of steps focused on edge detection. The extracted angles were not significantly different from angles measured manually by three independent observers, thus being a valid method to measure bank angles. Image quality, high wind speeds, and sunlight all influenced the accuracy of angle estimates, but post‐processing eliminated most of these errors. Birds flew most often with cross‐winds (58%) and tailwinds (39%), resulting in skewed distributions of bank angles when birds turned into the wind more often. Higher wind speeds resulted in extreme bank angles (maximum observed was 94°). We present a novel method for measuring postural data from seabirds that can be used to describe the fine‐scale movements of the dynamic‐soaring cycle. Birds appeared to alter their bank angle in response to varying wind conditions to counter wind drift associated with the prevailing westerly winds in the Southern Ocean. These data, in combination with fine‐scale positional data, may lead to new insights into dynamic‐soaring flight.     

Assessing Greater Sage-Grouse Selection of Brood-Rearing Habitat Using Remotely-Sensed Imagery: Can Readily Available High-Resolution Imagery Be Used to Identify Brood-Rearing Habitat Across a Broad Landscape?

Greater sage-grouse populations have decreased steadily since European settlement in western North America. Reduced availability of brood-rearing habitat has been identified as a limiting factor for many populations. We used radio-telemetry to acquire locations of sage-grouse broods from 1998 to 2012 in Strawberry Valley, Utah. Using these locations and remotely-sensed NAIP (National Agricultural Imagery Program) imagery, we 1) determined which characteristics of brood-rearing habitat could be used in widely available, high resolution imagery 2) assessed the spatial extent at which sage-grouse selected brood-rearing habitat, and 3) created a predictive habitat model to identify areas of preferred brood-rearing habitat. We used AIC model selection to evaluate support for a list of variables derived from remotely-sensed imagery. We examined the relationship of these explanatory variables at three spatial extents (45, 200, and 795 meter radii). Our top model included 10 variables (percent shrub, percent grass, percent tree, percent paved road, percent riparian, meters of sage/tree edge, meters of riparian/tree edge, distance to tree, distance to transmission lines, and distance to permanent structures). Variables from each spatial extent were represented in our top model with the majority being associated with the larger (795 meter) spatial extent. When applied to our study area, our top model predicted 75% of naïve brood locations suggesting reasonable success using this method and widely available NAIP imagery. We encourage application of our methodology to other sage-grouse populations and species of conservation concern.