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.

• Klíčová slova
• CJS model, caudal autotomy, escape rate, predation risk, predator pressure, reptile,
• Publikační typ
• časopisecké články MeSH

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.

• MeSH
• buněčná diferenciace MeSH
• fluorescenční barviva MeSH
• kardiomyocyty cytologie   ultrastruktura   MeSH
• konfokální mikroskopie metody   MeSH
• krysa rodu Rattus MeSH
• modely kardiovaskulární MeSH
• neuronové sítě MeSH
• počítačové zpracování obrazu metody   MeSH
• sarkolema ultrastruktura   MeSH
• strojové učení MeSH
• umělá inteligence MeSH
• zvířata MeSH
• Check Tag
• krysa rodu Rattus MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• fluorescenční barviva MeSH

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.

• Klíčová slova
• Chiroptera, fungal load, fuzzy regression, histopathology, thermal preference, white-nose syndrome,
• Publikační typ
• časopisecké články MeSH