Forecasting daily total pollen concentrations on a global scale.

BACKGROUND: There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts. METHODS: The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values. RESULTS: The best pollen forecasts include Mexico City (R2(DL_7) ≈ .7), and Santiago (R2(DL_7) ≈ .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈ .4) and Seoul (R2(DL_7) ≈ .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan. CONCLUSIONS: This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts.

Arthropods dataset from different genetically modified maize events and associated controls.

Arthropods from four genetically modified (GM) maize hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant+herbicide tolerant and coleopteran resistant and herbicide tolerant) and non-GM varieties were sampled during a two-year field assessment. A total number of 363 555 arthropod individuals were collected. This represents the most comprehensive arthropod dataset from GM maize, and together with weed data, is reasonable to determine functional groups of arthropods and interactions between species. Trophic groups identified from both phytophagous and predatory arthropods were previously considered non-target organisms on which possible detrimental effects of Bacillus thuringiensis (Bt) toxins may have been directly (phytophagous species) or indirectly (predators) detected. The high number of individuals and species and their dynamics through the maize growing season can predict that interactions are highly correlational, and can thus be considered a useful tool to assess potential deleterious effects of Bt toxins on non-target organisms, serving to develop biosafety risk hypotheses for invertebrates exposed to GM maize plants.

Effects of genetically modified maize events expressing Cry34Ab1, Cry35Ab1, Cry1F, and CP4 EPSPS proteins on arthropod complex food webs.

Four genetically modified (GM) maize (Zea mays L.) hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant and herbicide tolerant, coleopteran and herbicide tolerant) and its non-GM control maize stands were tested to compare the functional diversity of arthropods and to determine whether genetic modifications alter the structure of arthropods food webs. A total number of 399,239 arthropod individuals were used for analyses. The trophic groups' number and the links between them indicated that neither the higher magnitude of Bt toxins (included resistance against insect, and against both insects and glyphosate) nor the extra glyphosate treatment changed the structure of food webs. However, differences in the average trophic links/trophic groups were detected between GM and non-GM food webs for herbivore groups and plants. Also, differences in characteristic path lengths between GM and non-GM food webs for herbivores were observed. Food webs parameterized based on 2-year in-field assessments, and their properties can be considered a useful and simple tool to evaluate the effects of Bt toxins on non-target organisms.

Effects of tramadol and O-demethyl-tramadol on human 5-HT reuptake carriers and human 5-HT3A receptors: a possible mechanism for tramadol-induced early emesis.

([3H]5-HT)-uptake and patch-clamp techniques were used to study the actions of (+) and (-) tramadol and the active metabolites of tramadol, (+) and (-) O-demethyl-tramadol on the human serotonin (5-HT) transporter and the human 5-HT3A receptor, stably expressed in HEK-293 cells. The (+) and (-) enantiomers of tramadol suppressed the human 5-HT transporter concentration-dependently (IC50=1.0 and 0.8 microM, respectively), resulting in 97% and 87% transport inhibition at their respective initial plasma concentrations (9.5 microM). The (+) and (-) enantiomers of the active tramadol metabolite were less potent than tramadol in inhibiting the human 5-HT transporter (IC50=15 and 44 microM, respectively), resulting in 19.2% and 4.8% transport inhibition at their highest plasma concentrations (2.5 microM). In contrast to their potent suppression of the 5-HT transporter, both, (+) and (-) tramadol inhibited 5-HT (30 microM)-induced currents only at substantially higher concentrations (IC50=199 and 251 microM, respectively), resulting in only 6% and 4% inhibition at the initial maximum plasma concentration. A similar low potent inhibition of human 5-HT(3A) receptors was found for (+) and (-) O-demethyl-tramadol (IC50=158 and 63 microM, respectively). In conclusion, at clinical plasma concentrations tramadol potently suppresses the human 5-HT transporter, whereas it has only a slight effect on the human 5-HT3A receptor. The results are compatible with a possible mechanism for tramadol-induced early emesis involving the serotonergic system.