Polyphyly of Asian Tree Toads,Genus Pedostibes Günther, 1876 (Anura: Bufonidae), and the Description of a New Genus from Southeast Asia

The Asian Tree Toad genus Pedostibes, as currently understood, exhibits a conspicuously disjunct distribution, posing several immediate questions relating to the biogeography and taxonomy of this poorly known group. The type species, P. tuberculosus and P. kempi, are known only from India, whereas P. hosii, P. rugosus, and P. everetti are restricted to Southeast Asia. Several studies have shown that these allopatric groups are polyphyletic, with the Indian Pedostibes embedded within a primarily South Asian clade of toads, containing the genera Adenomus, Xanthophryne, and Duttaphrynus. Southeast Asian Pedostibes on the other hand, are nested within a Southeast Asian clade, which is the sister lineage to the Southeast Asian river toad genus Phrynoidis. We demonstrate that Indian and Southeast Asian Pedostibes are not only allopatric and polyphyletic, but also exhibit significant differences in morphology and reproductive mode, indicating that the Southeast Asian species’ are not congeneric with the true Pedostibes of India. As a taxonomic solution, we describe a new genus, Rentapia gen. nov. to accommodate the Southeast Asian species.     

Assay of 1L-myo-inositol-1-phosphatase using a fluorometric method.

1L-myo-Inositol-1-phosphatase, an enzyme purified from brain tissues, catalyzes the dephosphorylation of 1L-myo-inositol 1-phosphate. This enzyme has become the subject of intense research interest, since myo-inositol is needed for the resynthesis of phosphatidylinositol. We have developed a sensitive fluorometric assay for detecting the activity of 1L-myo-inositol-1-phosphatase. The assay is based on o-aminobenzoyl beta-glycerophosphate fluorescence, according to the following principles: (I) The fluorescence yield of o-aminobenzoyl beta-glycerophosphate is increased by 2.75-fold in the presence of saturating concentrations of bovine serum albumin. (II) o-Aminobenzoyl beta-glycerophosphate has the same fluorescence yield as o-aminobenzoyl glycerol, but the latter does not bind to bovine serum albumin. (III) Dephosphorylation of the substrate, catalyzed by the monophosphatase, makes less o-aminobenzoyl beta-glycerophosphate available for binding to bovine serum albumin, thereby producing a decrease in the fluorescence intensity.     

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.     

‘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.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

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.