Modelling invasive pathogen load from non-destructive sampling data.

Where microbes colonizing skin surface may help maintain organism homeostasis, those that invade living skin layers cause disease. In bats, white-nose syndrome is a fungal skin infection that affects animals during hibernation and may lead to mortality in severe cases. Here, we inferred the amount of fungus that had invaded skin tissue of diseased animals. We used simulations to estimate the unobserved disease severity in a non-lethal wing punch biopsy and to relate the simulated pathology to the measured fungal load in paired biopsies. We found that a single white-nose syndrome skin lesion packed with spores and hyphae of the causative agent, Pseudogymnoascus destructans, contains 48.93 pg of the pathogen DNA, which amounts to about 1560 P destructans genomes in one skin lesion. Relating the information to the known UV fluorescence in Nearctic and Palearctic bats shows that Nearctic bats carry about 1.7 µg of fungal DNA per cm2, whereas Palearctic bats have 0.04 µg cm-2 of P. destructans DNA. With the information on the fungal load that had invaded the host skin, the researchers can now calculate disease severity as a function of invasive fungal growth using non-destructive UV light transillumination of each bat's wing membranes. Our results will enable and promote thorough disease severity assessment in protected bat species without the need for extensive animal and laboratory labor sacrifices.

Numerous cold arousals and rare arousal cascades as a hibernation strategy in European Myotis bats.

Hibernating bats optimise the duration of torpor bouts and arousals in relation to hibernaculum microclimatic conditions and fat reserves. Clustering has significant physiological and ecological benefits, promoting successful hibernation of individuals. Such aggregations may help maintain optimal temperatures, allowing better energy utilisation than in solitarily bats. However, aroused bats in a cluster could conceivably disturb those still hibernating, starting an energy-demanding arousal process. Our study was conducted over two winters in two different hibernacula (cave and mine) in the Czech Republic, where Greater mouse-eared bats (Myotis myotis) have previously been diagnosed with white-nose syndrome. In 118 arousal episodes we recorded 193 individual arousals in which a warming phase was observed, 135 (69.9%) being cold arousals, where bats ceased increasing their body temperatures at ≤ 10 °C. The remaining arousals were standard normothermic arousals, where body (fur) surface temperatures reached > 20 °C. Cold arousals occurred during the mid- and late hibernation periods, suggesting they were a response to disturbance by a neighbour in the same cluster. Arousal cascades, where bats aroused in series, were rare (12.7%) and reached a maximum in mid-January. Our data suggest that Myotis bats prolong their torpor bouts using numerous cold arousals but few arousal cascades. Upon arrival of a bat, the clustered bats show tolerance to disturbing by conspecifics.

High predation risk decimates survival during the reproduction season.

Predators attack conspicuous prey phenotypes that are present in the environment. Male display behavior of conspicuous nuptial coloration becomes risky in the presence of a predator, and adult males face higher predation risk. High predation risk in one sex will lead to low survival and sex ratio bias in adult cohorts, unless the increased predation risk is compensated by higher escape rate.Here, we tested the hypothesis that sand lizards (Lacerta agilis) have sex-specific predation risk and escape rate. We expected the differences to manifest in changes in sex ratio with age, differences in frequency of tail autotomy, and in sex-specific survival rate.We developed a statistical model to estimate predation risk and escape rate, combining the observed sex ratio and frequency of tail autotomy with likelihood-based survival rate. Using Bayesian framework, we estimated the model parameters. We projected the date of the tail autotomy events from growth rates derived from capture-recapture data measurements.We found statistically stable sex ratio in age groups, equal frequency of tail regenerates between sexes, and similar survival rate. Predation risk is similar between sexes, and escape rate increases survival by about 5%. We found low survival rate and a low number of tail autotomy events in females during months when sand lizards mate and lay eggs, indicating high predator pressure throughout reproduction. Our data show that gravid females fail to escape predation.The risks of reproduction season in an ectotherm are a convolution of morphological changes (conspicuous coloration in males and body allometry changes in gravid females), behavior (nuptial displays), and environmental conditions which challenge lizard thermal performance. Performance of endotherm predators in cold spring months endangers gravid females more than displaying males in bright nuptial coloration.

Automatic assessment of the cardiomyocyte development stages from confocal microscopy images using deep convolutional networks.

Computer assisted image acquisition techniques, including confocal microscopy, require efficient tools for an automatic sorting of vast amount of generated image data. The complexity of the classification process, absence of adequate tools, and insufficient amount of reference data has made the automated processing of images challenging. Mastering of this issue would allow implementation of statistical analysis in research areas such as in research on formation of t-tubules in cardiac myocytes. We developed a system aimed at automatic assessment of cardiomyocyte development stages (SAACS). The system classifies confocal images of cardiomyocytes with fluorescent dye stained sarcolemma. We based SAACS on a densely connected convolutional network (DenseNet) topology. We created a set of labelled source images, proposed an appropriate data augmentation technique and designed a class probability graph. We showed that the DenseNet topology, in combination with the augmentation technique is suitable for the given task, and that high-resolution images are instrumental for image categorization. SAACS, in combination with the automatic high-throughput confocal imaging, will allow application of statistical analysis in the research of the tubular system development or remodelling and loss.

Hibernation temperature-dependent Pseudogymnoascus destructans infection intensity in Palearctic bats.

White-nose syndrome (WNS) is a fungal disease caused by Pseudogymnoascus destructans that is devastating to Nearctic bat populations but tolerated by Palearctic bats. Temperature is a factor known to be important for fungal growth and bat choice of hibernation. Here we investigated the effect of temperature on the pathogenic fungal growth in the wild across the Palearctic. We modelled body surface temperature of bats with respect to fungal infection intensity and disease severity and were able to relate this to the mean annual surface temperature at the site. Bats that hibernated at lower temperatures had less fungal growth and fewer skin lesions on their wings. Contrary to expectation derived from laboratory P. destructans culture experiments, natural infection intensity peaked between 5 and 6°C and decreased at warmer hibernating temperature. We made predictive maps based on bat species distributions, temperature and infection intensity and disease severity data to determine not only where P. destructans will be found but also where the infection will be invasive to bats across the Palearctic. Together these data highlight the mechanistic model of the interplay between environmental and biological factors, which determine progression in a wildlife disease.

Robust Grape Detector Based on SVMs and HOG Features.

Detection of grapes in real-life images is a serious task solved by researchers dealing with precision viticulture. In the case of white wine varieties, grape detectors based on SVMs classifiers, in combination with a HOG descriptor, have proven to be very efficient. Simplified versions of the detectors seem to be the best solution for practical applications. They offer the best known performance versus time-complexity ratio. As our research showed, a conversion of RGB images to grayscale format, which is implemented at an image preprocessing level, is ideal means for further improvement of performance of the detectors. In order to enhance the ratio, we explored relevance of the conversion in a context of a detector potential sensitivity to a rotation of berries. For this purpose, we proposed a modification of the conversion, and we designed an appropriate method for a tuning of such modified detectors. To evaluate the effect of the new parameter space on their performance, we developed a specialized visualization method. In order to provide accurate results, we formed new datasets for both tuning and evaluation of the detectors. Our effort resulted in a robust grape detector which is less sensitive to image distortion.