COVID-19, systemic crisis, and possible implications for the wild meat trade in sub-Saharan Africa

Wild animals play an integral and complex role in the economies and ecologies of many countries across the globe, including those of West and Central Africa, the focus of this policy perspective. The trade in wild meat, and its role in diets, have been brought into focus as a consequence of discussions over the origins of COVID-19. As a result, there have been calls for the closure of China’s “wet markets”; greater scrutiny of the wildlife trade in general; and a spotlight has been placed on the potential risks posed by growing human populations and shrinking natural habitats for animal to human transmission of zoonotic diseases. However, to date there has been little attention given to what the consequences of the COVID-19 economic shock may be for the wildlife trade; the people who rely on it for their livelihoods; and the wildlife that is exploited. In this policy perspective, we argue that the links between the COVID-19 pandemic, rural livelihoods and wildlife are likely to be more complex, more nuanced, and more far-reaching, than is represented in the literature to date. We develop a causal model that tracks the likely implications for the wild meat trade of the systemic crisis triggered by COVID-19. We focus on the resulting economic shockwave, as manifested in the collapse in global demand for commodities such as oil, and international tourism services, and what this may mean for local African economies and livelihoods. We trace the shockwave through to the consequences for the use of, and demand for, wild meats as households respond to these changes. We suggest that understanding and predicting the complex dynamics of wild meat use requires increased collaboration between environmental and resource economics and the ecological and conservation sciences

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Dynamic water quality modelling and uncertainty analysis of phytoplankton and nutrient cycles for the upper South Saskatchewan River

The surface water quality of the upper South Saskatchewan River was modelled using Water Quality Analysis Simulation Program (WASP) 7.52. Model calibration and validation were based on samples taken from four long-term water quality stations during the period 2007–2009. Parametric sensitivities in winter and summer were examined using root mean square error (RMSE) and relative entropy. The calibration and validation results show good agreement between model prediction and observed data. The two sensitivity methods confirmed pronounced parametric sensitivity to model state variables in summer compared to winter. Of the 24 parameters examined, dissolved oxygen (DO) and ammonia (NH3-N) are the most influenced variables in summer. Instream kinetic processes including nitrification, nutrient uptake by algae and algae respiration induce a higher sensitivity on DO in summer than in winter. Moreover, in summer, soluble reactive phosphorus (SRP) and chlorophyll-a (Chla) variables are more sensitive to algal processes (nutrient uptake and algae death). In winter however, there exists some degree of sensitivity of algal processes (algae respiration and nutrient uptake) to DO and NH3-N. Results of this study provide information on the state of the river water quality which impacts Lake Diefenbaker and the need for additional continuous monitoring in the river. The results of the sensitivity analysis also provide guidance on most sensitive parameters and kinetic processes that affect eutrophication for preliminary surface water quality modelling studies in cold regions