Entomopathogenic fungi are gaining acceptance in Integrated Pest Management (IPM) systems as effective and environmental safety biological control agents to protect a great variety of crops against ...pest insects. Many of these insect-pathogenic fungi can establish themselves as endophytes and thereby may induce the plant immune system. The activation of plant defenses by the fungal endophytic colonization can have a direct impact on herbivores and plant pathogens. An integral component of many plant defense responses is also the release of volatile organic compounds, which may serve as an indirect defense by attracting the natural enemies of herbivores. Here we investigated the effect of endophytic colonization by the entomopathogenic fungus
Beauveria bassiana
on the volatile emission by melon and cotton plants, either unharmed or after being damaged by sap-sucking aphids or leaf chewing caterpillars. We found that when the plants are colonized by
B. bassiana
they emit a different blend of volatile compounds compared to uncolonized control plants. Some of the emitted compounds have been reported previously to be released in response to herbivory and have been implicated in natural enemy attraction. Several of the compounds are also known to have antimicrobial properties. Therefore, endophytic colonization by
B. bassiana
might help to not only direct control insect pests but also increase the resistance of plants against agronomically important pests and phytopathogens.
•The problem of remote weed mapping via machine learning is considered.•Unmanned aerial vehicles are used to capture maize and sunflower field images.•The proposed method considers pattern and ...feature selection techniques.•The final model requires few user information to generalise to new areas.•There are features of great influence for the classification of both crops.
This paper approaches the problem of weed mapping for precision agriculture, using imagery provided by Unmanned Aerial Vehicles (UAVs) from sunflower and maize crops. Precision agriculture referred to weed control is mainly based on the design of early post-emergence site-specific control treatments according to weed coverage, where one of the most important challenges is the spectral similarity of crop and weed pixels in early growth stages. Our work tackles this problem in the context of object-based image analysis (OBIA) by means of supervised machine learning methods combined with pattern and feature selection techniques, devising a strategy for alleviating the user intervention in the system while not compromising the accuracy. This work firstly proposes a method for choosing a set of training patterns via clustering techniques so as to consider a representative set of the whole field data spectrum for the classification method. Furthermore, a feature selection method is used to obtain the best discriminating features from a set of several statistics and measures of different nature. Results from this research show that the proposed method for pattern selection is suitable and leads to the construction of robust sets of data. The exploitation of different statistical, spatial and texture metrics represents a new avenue with huge potential for between and within crop-row weed mapping via UAV-imagery and shows good synergy when complemented with OBIA. Finally, there are some measures (specially those linked to vegetation indexes) that are of great influence for weed mapping in both sunflower and maize crops.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We use molecular simulations to analyze the preferential adsorption sites of molecules that differ in size, shape, and polarizability in Cu-BTC metal organic framework. The cage system of the ...framework can be exploited to enhance adsorption of small gases. We find that nonpolar molecules adsorb preferentially in the small tetrahedral cages, whereas alcohols and water molecules adsorb close to the copper atoms in one of the big cages. Blocking potentially enhances selective adsorption and separation and we therefore investigate how to block these cages in a practical manner. We propose to use ionic liquids for it and we find that the addition of these components reduces the adsorption of polar molecules near the open metal centers. For this reason, the presence of ionic liquids reduces the attack of the molecules of water to the metallic centers improving the framework stability.
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IJS, KILJ, NUK, PNG, UL, UM
We report a molecular simulation study aimed to ascertain the effect exerted in gas adsorption when room-temperature ionic liquids (RTILs) are added into the pores of the Cu-BTC metal-organic ...framework (MOF). Carbon dioxide, methane, nitrogen, and their mixtures are studied. We take into account the influence of the type of anion and the relative amount of RTILs used. It is observed that the presence of RTILs in the MOF pores enhances significantly CO2 adsorption at low pressures, whereas methane and nitrogen adsorption is unaffected.
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IJS, KILJ, NUK, PNG, UL, UM
The deep sea plays a critical role in global climate regulation through uptake and storage of heat and carbon dioxide. However, this regulating service causes warming, acidification and deoxygenation ...of deep waters, leading to decreased food availability at the seafloor. These changes and their projections are likely to affect productivity, biodiversity and distributions of deep‐sea fauna, thereby compromising key ecosystem services. Understanding how climate change can lead to shifts in deep‐sea species distributions is critically important in developing management measures. We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold‐water coral and commercially important deep‐sea fish species under present‐day (1951–2000) environmental conditions and to project changes under severe, high emissions future (2081–2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean. Our models projected a decrease of 28%–100% in suitable habitat for cold‐water corals and a shift in suitable habitat for deep‐sea fishes of 2.0°–9.9° towards higher latitudes. The largest reductions in suitable habitat were projected for the scleractinian coral Lophelia pertusa and the octocoral Paragorgia arborea, with declines of at least 79% and 99% respectively. We projected the expansion of suitable habitat by 2100 only for the fishes Helicolenus dactylopterus and Sebastes mentella (20%–30%), mostly through northern latitudinal range expansion. Our results projected limited climate refugia locations in the North Atlantic by 2100 for scleractinian corals (30%–42% of present‐day suitable habitat), even smaller refugia locations for the octocorals Acanella arbuscula and Acanthogorgia armata (6%–14%), and almost no refugia for P. arborea. Our results emphasize the need to understand how anticipated climate change will affect the distribution of deep‐sea species including commercially important fishes and foundation species, and highlight the importance of identifying and preserving climate refugia for a range of area‐based planning and management tools.
We used environmental niche modelling to predict the habitat suitability for key cold‐water coral and commercially important deep‐sea fish species under present‐day environmental conditions and to forecast changes under future climate projections (RCP8.5) for the North Atlantic Ocean. Our models forecasted a significant decrease in suitable habitat for cold‐water corals and poleward expansion in suitable habitat for deep‐sea fishes in response to climate change. Our results emphasize the need to understand how climate change will affect the distribution of deep‐sea species and highlight the importance of identifying and preserving climate refugia for a range of area‐based planning and management tools.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Global bioclimatic datasets are being widely used in ecological research to estimate the potential distribution of species using Climate Envelope Models (CEMs). These datasets are easily available ...and offer high resolution information for all land areas globally. However, they have not been tested rigorously in smaller regions, and their use in regional CEM studies may pose problems derived from their poor representation of local climate features. Moreover, these problems may be enhanced when using CEMs for future climate projections—a topic of current active research—due to the uncertainty derived from the future altered climate scenarios.
In this paper we use distributional data of European beech (Fagus sylvatica) in Northern Iberian Peninsula to analyze the discrepancies of the CEMs (predictive skill, variable importance and consistency using different predictor subsets) resulting from three alternative public, high-resolution climate datasets: a benchmarking regional climate dataset developed for the area of study (UC), the University of Barcelona Atlas for the Iberian Peninsula (UAB) and the worldwide WorldClim bioclimatic dataset (WC). The same CEM techniques (multiple logistic regression and multivariate adaptive regression splines) were applied to the different datasets, showing that the quality of the baseline climate has a great impact on the resulting models, as manifested by the different contributions of the bioclimatic predictors to the resulting models. Artifactual bioclimatic variables were found in some datasets, representing topographical features and spatial gradients, rather than true climatic patterns, thus significantly contributing to the models, although not for the right reasons. This causes a misleading model interpretation and problems for extrapolation in future climate conditions, as evidenced analyzing the future projections obtained using state-of-the-art regional climate projections from the ENSEMBLES project.
•Three public high-resolution bioclimatic datasets are intercompared for niche modelling.•Regional deficiencies of WorldClim lead to misleading distribution models.•Model problems are not readily apparent in terms of predictive performance.•Serious inconsistencies arise when projecting models into future climate conditions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Scope
Little is known about the changes that a very‐low‐calorie ketogenic diet (VLCKD) produces in gut microbiota or the effect of synbiotics during the diet. The aim of this study is to evaluate ...changes in gut microbiota produced by a VLCKD and synbiotic supplementation.
Methods and results
A randomized, single‐blind, parallel‐design trial is conducted in 33 obese patients who follow a weight‐loss program (PnK‐Method) that include a VLCKD followed by a low‐calorie diet (LCD). Subjects are randomly allocated to three groups: one supplemented with synbiotics, a second group supplemented with a placebo during the VLCKD and synbiotics during the LCD phase, and a control group given a placebo.
Although symbiotic administration do not produce an effect on microbial diversity, an increase in short‐chain fatty aciding producing bacteria and anti‐inflammatory mediator signals such as Odoribacter and Lachnospira is shown. The administration of Bifidobacterium animalis subsp. lactis and prebiotics fiber during the LCD is significantly associated with the percentage of weight loss and change in glucose, C‐reactive protein and lipopolysaccharide‐binding protein.
Conclusions
VLCKD produces important changes in gut microbiota. The administration of synbiotics during VLCKD can improve weight loss through the amelioration of inflammation, which may be mediated by the gut microbiota.
Gut microbiota changes produced by a very‐low‐calorie ketogenic diet in obese patients are shown. Although the administration of synbiotics during the intervention does not have an effect on microbial diversity, they can contribute to the weight loss through the amelioration of the inflammation. The inflammation improvement can be mediated through the gut microbiota.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Valproic acid (VPA) has shown beneficial effects in vitro against SARS-CoV-2 infection, but no study has analyzed its efficacy in the clinical setting.
This multicenter, retrospective study included ...165 adult patients receiving VPA at the time of admission to hospital, and 330 controls matched for sex, age and date of admission. A number of clinical, outcome and laboratory parameters were recorded to evaluate differences between the two groups. Four major clinical endpoints were considered: development of lung infiltrates, in-hospital respiratory worsening, ICU admissions and death.
VPA-treated patients had higher lymphocyte (P<0.0001) and monocyte (P = 0.0002) counts, and lower levels of diverse inflammatory parameters, including a composite biochemical severity score (P = 0.016). VPA patients had shorter duration of symptoms (P<0.0001), were more commonly asymptomatic (P = 0.016), and developed less commonly lung infiltrates (65.8%/88.2%, P<0.0001), respiratory worsening (20.6%/30.6%, P = 0.019) and ICU admissions (6.1%/13.0%, P = 0.018). There was no difference in survival (84.8%/88.8%, P = 0.2), although death was more commonly related to non-COVID-19 causes in the VPA group (36.0%/10.8%, P = 0.017). The cumulative hazard for developing adverse clinical endpoints was higher in controls than in the VPA group for infiltrates (P<0.0001), respiratory worsening (P<0.0001), and ICU admissions (P = 0.001), but not for death (0.6). Multivariate analysis revealed that VPA treatment was independently protective for the development of the first three clinical endpoints (P = 0.0002, P = 0.03, and P = 0.025, respectively), but not for death (P = 0.2).
VPA-treated patients seem to develop less serious COVID-19 than control patients, according to diverse clinical endpoints and laboratory markers.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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