Antifungal and anti-aflatoxigenic activity of Heliopsis longipes roots and affinin/spilanthol against Aspergillus parasiticus by downregulating the expression of alfD and aflR genes of the aflatoxins biosynthetic pathway

Abstract

In the present study, ethanolic extract from Heliopsis longipes roots and affinin/spilanthol against Aspergillus parasiticus growth and aflatoxins production were studied in relation to the expression of aflD and aflR, two key genes of aflatoxins biosynthetic pathway. Phytochemical analysis of the ethanolic extract by GC-EIMS identified affinin/spilanthol (7.84?±?0.27?mg g^?1) as the most abundant compounds in H. longipes roots. The antifungal and anti-aflatoxigenic assays showed that affinin/spilanthol at 300?µg mL^?1 produced the higher inhibition of radial growth (95%), as well as, the higher aflatoxins production inhibition (61%) in comparison to H. longipes roots (87% and 48%, respectively). qRT-PCR revealed that the expression of aflD and aflR genes showed a higher downregulation in affinin/spilanthol at 300?µg mL^?1. The expression ratio of alfD was suppressed by affinin/spilanthol in 79% and aflR in 84%, while, a lower expression ratio suppressed by H. longipes was obtained, alfD (55%) and aflR (59%). Affinin/spilanthol possesses higher antifungal and anti-aflatoxigenic activity against A. parasiticus rather than H. longipes roots, and this anti-aflaxotigenic activity occurring via downregulation of the aflD and aflR genes. Thus, H. longipes roots and affinin/spilanthol can be considered potent antifungal agents against aflatoxigenic fungus, especially, affinin/spilanthol.     

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.     

The feasibility of concentrated rural settlement in a context of post‐disaster reconstruction: a study of China

There is growing appreciation of the use of concentrated rural settlement as an effective means of implementing infrastructure projects and helping to achieve sustainable development in rural areas. This occurs in China through the exchange of rural residential land for urban construction. However, this policy has not been effective under normal circumstances (called development‐driven conditions) as frequently farmers are reluctant to accept such an exchange. By contrast, in a time of disaster, such as after the 2008 earthquake in Sichuan Province, China, rural victims have accepted this policy of rural residential land exchange. Employing game theory, this paper identifies the reasons for the different outcomes and it contends that the implementation of concentrated rural settlement practice under disaster‐induced conditions is more effective than its introduction under development‐driven conditions. The results of the analysis indicate that, in China, concentrated rural settlement is feasible in a context of post‐disaster reconstruction.     

Spatio-temporal log-Gaussian Cox processes for modelling wildfire occurrence: the case of Catalonia, 1994–2008

Wildfires have become one of the principal environmental problems in the Mediterranean basin. While fire plays an important role in most terrestrial plant ecosystems, the potential hazard that it represents for human lives and property has led to the application of fire exclusion policies that, in the long term, have caused severe damage, mainly due to the increase of fuel loadings in forested areas, in some forest systems. The lack of an easy solution to forest fire management highlights the importance of preventive tasks. The observed spatio-temporal pattern of wildfire occurrences may be idealized as a realization of some stochastic process. In particular, we may use a space–time point pattern approach for the analysis and inference process. We studied wildfires in Catalonia, a region in the north-east of the Iberian Peninsula, and we analyzed the spatio-temporal patterns produced by those wildfire incidences by considering the influence of covariates on trends in the intensity of wildfire locations. A total of 3,166 wildfires from 1994–2008 have been recorded. We specified spatio-temporal log-Gaussian Cox process models. Models were estimated using Bayesian inference for Gaussian Markov Random Field through the integrated nested Laplace approximation algorithm. The results of our analysis have provided statistical evidence that areas closer to humans have more human induced wildfires, areas farther have more naturally occurring wildfires. We believe the methods presented in this paper may contribute to the prevention and management of those wildfires which are not random in space or time.     

Mobilization of arsenic and other trace elements of health concern in groundwater from the Salí River Basin, Tucumán Province, Argentina

The Salí River Basin in north-west Argentina (7,000 km²) is composed of a sequence of Tertiary and Quaternary loess deposits, which have been substantially reworked by fluvial and aeolian processes. As with other areas of the Chaco-Pampean Plain, groundwater in the basin suffers a range of chemical quality problems, including arsenic (concentrations in the range of 12.2–1,660 μg L⁻¹), fluoride (50–8,740 μg L⁻¹), boron (34.0–9,550 μg L⁻¹), vanadium (30.7–300 μg L⁻¹) and uranium (0.03–125 μg L⁻¹). Shallow groundwater (depths up to 15 m) has particularly high concentrations of these elements. Exceedances above WHO (2011) guideline values are 100% for As, 35% for B, 21% for U and 17% for F. Concentrations in deep (>200 m) and artesian groundwater in the basin are also often high, though less extreme than at shallow depths. The waters are oxidizing, with often high bicarbonate concentrations (50.0–1,260 mg L⁻¹) and pH (6.28–9.24). The ultimate sources of these trace elements are the volcanic components of the loess deposits, although sorption reactions involving secondary Al and Fe oxides also regulate the distribution and mobility of trace elements in the aquifers. In addition, concentrations of chromium lie in range of 79.4–232 μg L⁻¹ in shallow groundwater, 129–250 μg L⁻¹ in deep groundwater and 110–218 μg L⁻¹ in artesian groundwater. All exceed the WHO guideline value of 50 μg L⁻¹. Their origin is likely to be predominantly geogenic, present as chromate in the ambient oxic and alkaline aquifer conditions.     

An integrative response by Mytilus chilensis to the toxic dinoflagellate Alexandrium catenella

Physiological responses of Mytilus chilensis exposed to the toxic dinoflagellate Alexandrium catenella were measured over 21 days in the laboratory and were compared with control mussels not exposed to the dinoflagellate. Mussels were collected from culturing ropes at Yaldad Bay, southern Chile (43o08′S 73o44′W), in August 2004 and acclimated to laboratory conditions for one week prior to the experiment. After 8 days, the paralytic shellfish poisoning (PSP) toxins (i.e. saxitoxin) in the tissues of exposed mussels exceeded safe levels for human consumption. Clearance rates, ingestion of organic matter, and absorption efficiency of exposed mussels were significantly lower than those of controls on day 0, but this was followed by an increase on day 3. The exposed mussels also increased their excretion rate over time, and this increase was significantly correlated with the accumulation of PSP toxins in their tissues. Oxygen consumption was not affected by the PSP toxins. The scope for growth (SFG) on day 0 was negative in exposed mussels, but it increased during the experiment. Although feeding activity and absorption efficiency were adversely affected during the first few days of exposure to PSP toxins from A. catenella in the laboratory, the M. chilensis cultured in Yaldad Bay may have evolved mechanisms that allow them to exploit the toxic dinoflagellate as a food source.     

Modeling high-frequency position data of large herbivores with a phase-state model

Understanding the rules and factors that drive the foraging behavior of large herbivores is important to describe their interaction with the landscape at various spatial scales. Some unresolved questions refer to landscape-behavioral interactions that result in oriented or random search in seasonally changing landscapes. Remotely sensed position data indicate that herbivores select local patches of heterogeneous landscapes depending on a complex host of dynamically varying animal and environmental conditions. Since foraging paths consist in successions of relatively short steps, increasing the frequency at which position information is acquired would contribute to entangle the mechanisms resulting in herbivores’ foraging paths. We addressed the question whether herbivores would obtain information at a patch scale that would modify their distribution at a landscape scale based on directed movement or navigation ability. We considered a set of 100,000 high-frequency (1 min intervals) position data of several free-ranging sheep (Ovis aries) at a seasonal-varying range (Patagonian Monte, Argentina) and observed their movements at landscape and at single vegetation patch scales. At a landscape scale, we inspected the spatial co-variation of seasonally varying forage offer and ewes’ movement speeds. At a patch scale, we developed a phase-state (P-S) model of movement cycles based on the occurrence of behavioral phases along foraging paths, and fitted it to the observed daily time series of ewes’ movement speeds. Ewes were preferentially distributed in areas with high forage offer during periods of low forage availability and the reverse occurred during the season of high forage availability. Parameters of the model of activity cycles amenable to control by ewes (duration of speed phases, time elapsed between speed cycles) did not covariate with forage offer, but varied significantly among ewes. The shape (kurtosis) parameter of the model of movement cycles, one which is unlikely under ewes’ control, co-varied significantly with spatial forage offer but did not differ among ewes. We conclude that ewes allocated foraging time along a series of similar movement efforts irrespective of forage availability at small patches. Average forage scarcity at multi-patch level increases the ratio of searching to feeding time. This results in apparent selective time allocation to richer forage areas but does not imply evidence for oriented movement at a landscape scale. We advance a behavioral-based definition of forage patches and discuss its implications in developing foraging theory and models. The P-S model applied to high-frequency position data of large herbivores substantially improves the interpretation of the factors controlling their time allocation in space with respect to previous models of herbivore spatial behavior by discriminating among behavioral-based and environmentally induced components of their movements.     

Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes

In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.