Electrophysiological characterization of Tityus obscurus β toxin 1 (To1) on Na+-channel isoforms

To1, previously named Tc49b, is a peptide neurotoxin isolated from venom of the scorpion Tityus obscurus that is responsible for lethal human poisoning cases in the Brazilian Amazonian region. Previously, To1 was shown to be lethal to mice and to change Na⁺ permeation in cerebellum granular neurons from rat brain. In addition, To1 did not affect Shaker B K⁺ channels. Based on sequence similarities, To1 was described as a β-toxin. In the present work, To1 was purified from T. obscurus venom and submitted to an electrophysiological characterization in human and invertebrate Na_V channels. The analysis of the electrophysiological experiments reveal that To1 enhances the open probability at more negative potentials of human Na_V 1.3 and 1.6, of the insect channel BgNa_V1 and of arachnid VdNa_V1 channel. In addition, To1 reduces the peak of Na⁺ currents in some of the Na_Vs tested. These results support the classification of the To1 as a β-toxin. A structure and functional comparison to other β-toxins that share sequence similarity to To1 is also presented.     

Weeds as a predominant food source: a review of the diet of common hamsters Cricetus cricetus in farmlands and urban habitats

相似文献   

Female variation in allocation of steroid hormones,antioxidants and fatty acids: a multilevel analysis in a wild passerine bird

The environment where an embryo develops can be influenced by components of maternal origin, which can shape offspring phenotypes and therefore maternal fitness. In birds that produce more than one egg per clutch, females differ in the concentration of components they allocate into the yolk along the laying sequence. However, identification of processes that shape female yolk allocation and thus offspring phenotype still remains a major challenge within evolutionary ecology. A way to increase our understanding is by acknowledging that allocation patterns can differ depending on the level of analysis, such as the population versus the among‐female (within‐population) level. We employed mixed models to analyze at both levels the variation in allocation along the laying sequence of four steroid hormones, three antioxidants, and four groups of fatty acids present in the egg yolks of wild great tits Parus major. We also quantified repeatabilities for each component to study female consistency. At a population level, the concentrations/proportions of five yolk components varied along the laying sequence, implying that the developmental environment is different for offspring developing in first versus last eggs. Females varied substantially in the mean allocation of components and in their plasticity along the laying sequence. For most components, these two parameters were negatively correlated. Females were also remarkably repeatable in their allocation. Overall, our data emphasize the need to account for female variation in yolk allocation along the laying sequence at multiple levels, as variation at a population level is underpinned by different individual patterns. Our findings also highlight the importance of considering both levels of analysis in future studies investigating the causes and fitness consequences of yolk compounds. Finally, our results on female repeatability confirm that analyzing one egg per nest is a suitable way to address the consequences of yolk resource deposition for the offspring.     

Influences of blackberry margins on population dynamics of Drosophila suzukii and grape infestation in adjacent vineyards

Understanding the dynamics of pest insect populations in relation to the presence of non‐crop habitats and infestation levels of adjacent crops is essential to develop sustainable pest management strategies. The invasive pest species Drosophila suzukii (Diptera: Drosophilidae) is able to utilize a broad range of host plants. In viticulture, scientific risk assessment for D. suzukii has only recently started and studies assessing the effects of field margins containing wild host plants on D. suzukii population dynamics and on infestation risks in adjacent vineyards are lacking. Thus, in a one‐year field study, the role of different field margins on fly abundance and crop infestation in adjacent vineyards of Vitis vinifera, variety “Pinot Noir,” were investigated. Different monitoring methods were conducted to assess fly distribution, sex ratio and grape infestation in 14 vineyards adjacent to field margins containing either blackberry (BB) Rubus spp. or non‐host (NH) plants. Our results show that blackberries strongly enhanced D. suzukii abundance within field margin vegetation all year long, whereas fly abundance in vineyards adjacent to BB margins was just enhanced in some seasonal periods. Moreover, the influence of BB margins was limited by distance. However, high fly numbers in BB field margins did result in zero egg infestation of “Pinot Noir” berries. These results may have important implications for winegrowers to make efficient management decisions: regardless of high abundance of adult D. suzukii, only grape berry monitoring can assess the actual infestation risk and the potential need to take management action.     

Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation

Focal sources (FS) are believed to be important triggers and a perpetuation mechanism for paroxysmal atrial fibrillation (AF). Detecting FS and determining AF sustainability in atrial tissue can help guide ablation targeting. We hypothesized that sustained rotors during FS-driven episodes indicate an arrhythmogenic substrate for sustained AF, and that non-invasive electrical recordings, like electrocardiograms (ECGs) or body surface potential maps (BSPMs), could be used to detect FS and AF sustainability. Computer simulations were performed on five bi-atrial geometries. FS were induced by pacing at cycle lengths of 120–270 ms from 32 atrial sites and four pulmonary veins. Self-sustained reentrant activities were also initiated around the same 32 atrial sites with inexcitable cores of radii of 0, 0.5 and 1 cm. FS fired for two seconds and then AF inducibility was tested by whether activation was sustained for another second. ECGs and BSPMs were simulated. Equivalent atrial sources were extracted using second-order blind source separation, and their cycle length, periodicity and contribution, were used as features for random forest classifiers. Longer rotor duration during FS-driven episodes indicates higher AF inducibility (area under ROC curve = 0.83). Our method had accuracy of 90.6±1.0% and 90.6±0.6% in detecting FS presence, and 93.1±0.6% and 94.2±1.2% in identifying AF sustainability, and 80.0±6.6% and 61.0±5.2% in determining the atrium of the focal site, from BSPMs and ECGs of five atria. The detection of FS presence and AF sustainability were insensitive to vest placement (±9.6%). On pre-operative BSPMs of 52 paroxysmal AF patients, patients classified with initiator-type FS on a single atrium resulted in improved two-to-three-year AF-free likelihoods (p-value < 0.01, logrank tests). Detection of FS and arrhythmogenic substrate can be performed from ECGs and BSPMs, enabling non-invasive mapping towards mechanism-targeted AF treatment, and malignant ectopic beat detection with likely AF progression.     

Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil

The dengue virus affects millions of people every year worldwide, causing large epidemic outbreaks that disrupt people’s lives and severely strain healthcare systems. In the absence of a reliable vaccine against dengue or an effective treatment to manage the illness in humans, most efforts to combat dengue infections have focused on preventing its vectors, mainly the Aedes aegypti mosquito, from flourishing across the world. These mosquito-control strategies need reliable disease activity surveillance systems to be deployed. Despite significant efforts to estimate dengue incidence using a variety of data sources and methods, little work has been done to understand the relative contribution of the different data sources to improved prediction. Additionally, scholarship on the topic had initially focused on prediction systems at the national- and state-levels, and much remains to be done at the finer spatial resolutions at which health policy interventions often occur. We develop a methodological framework to assess and compare dengue incidence estimates at the city level, and evaluate the performance of a collection of models on 20 different cities in Brazil. The data sources we use towards this end are weekly incidence counts from prior years (seasonal autoregressive terms), weekly-aggregated weather variables, and real-time internet search data. We find that both random forest-based models and LASSO regression-based models effectively leverage these multiple data sources to produce accurate predictions, and that while the performance between them is comparable on average, the former method produces fewer extreme outliers, and can thus be considered more robust. For real-time predictions that assume long delays (6–8 weeks) in the availability of epidemiological data, we find that real-time internet search data are the strongest predictors of dengue incidence, whereas for predictions that assume short delays (1–3 weeks), in which the error rate is halved (as measured by relative RMSE), short-term and seasonal autocorrelation are the dominant predictors. Despite the difficulties inherent to city-level prediction, our framework achieves meaningful and actionable estimates across cities with different demographic, geographic and epidemic characteristics.