Carbon and nitrogen isotopic similarity between the endangered Darwin's fox (Lycalopex fulvipes) and sympatric free-ranging dogs in Chiloé Island, Chile

Darwin's fox is an opportunistic omnivorous predator native to Chile classified as endangered by the IUCN Red List. Habitat use by Darwin's foxes can be negatively affected by the presence of free-ranging dogs that range freely across native and non-native habitats and can be a source of fox mortality. The objective of this study was to analyze the isotopic similarity of Darwin's fox and sympatric free-ranging dogs in Chiloé Island to determine the impact of anthropogenic environmental alterations on wild predators. We use hair samples to characterise and compare their δ¹³C and δ¹⁵N values and to evaluate isotopic similarity and isotope niches overlap. A generalised linear model was used to associate the isotope value with landscape variables (forest cover and vegetation type) and distance to the nearest house. We found no significant differences in δ¹³C or δ¹⁵N values between foxes and dogs, and a marginally significant isotope niche overlap (59.4 %). None of the selected variables at landscape and site scale were related to isotope values. Although our study is not a probe of direct contact between foxes and free-ranging dogs, the high isotopic similarity highlights the risk of pathogen spillover from free-ranging dogs to Darwin's foxes.

Marked host association and molecular evidence of limited transmission of ticks and fleas between sympatric wild foxes and rural dogs

Wild and domestic carnivores share ectoparasites, although molecular evidence is lacking. The goals of this study were to describe tick and flea infestation in sympatric free-ranging dogs Canis lupus familiaris (Linnaeus, 1758) (Carnivora: Canidae) and Andean foxes Lycalopex culpaeus (Molina, 1782) (Carnivora: Canidae) and to determine whether interspecific transmission occurs. Fleas and ticks retrieved from 79 foxes and 111 dogs in the human-dominated landscapes of central Chile were identified and a subset of specimens characterized by PCR and amplicon sequencing. Each ectoparasite species was clearly associated with a host: abundance and occurrence of Rhipicephalus sanguineus (Latreille 1806) (Acari: Ixodidae) and Ctenocephalides spp. (Siphonaptera: Pulicidae) were significantly higher in dogs than in foxes, whereas the opposite was true for Amblyomma tigrinum (Koch, 1844) (Acari: Ixodidae) and Pulex irritans (Linnaeus, 1758) (Siphonaptera: Pulicidae). Genetic analyses of a subset of ectoparasites revealed that dogs and foxes shared a limited number of nucleotide sequence types, suggesting that the interspecific transmission of these ectoparasites happens infrequently. Data also indicated that the ecological association and biological cycles of ticks and fleas determine the ectoparasite fauna of sympatric carnivores. In conclusion, our study shows that cross-species transmission should be assessed at a molecular level.

Automated segmentation of tissue images for computerized IHC analysis

This paper presents two automated methods for the segmentation of immunohistochemical tissue images that overcome the limitations of the manual approach as well as of the existing computerized techniques. The first independent method, based on unsupervised color clustering, recognizes automatically the target cancerous areas in the specimen and disregards the stroma; the second method, based on colors separation and morphological processing, exploits automated segmentation of the nuclear membranes of the cancerous cells. Extensive experimental results on real tissue images demonstrate the accuracy of our techniques compared to manual segmentations; additional experiments show that our techniques are more effective in immunohistochemical images than popular approaches based on supervised learning or active contours. The proposed procedure can be exploited for any applications that require tissues and cells exploration and to perform reliable and standardized measures of the activity of specific proteins involved in multi-factorial genetic pathologies.

Achieving the way for automated segmentation of nuclei in cancer tissue images through morphology-based approach: a quantitative evaluation

In this paper we address the problem of nuclear segmentation in cancer tissue images, that is critical for specific protein activity quantification and for cancer diagnosis and therapy. We present a fully automated morphology-based technique able to perform accurate nuclear segmentations in images with heterogeneous staining and multiple tissue layers and we compare it with an alternate semi-automated method based on a well established segmentation approach, namely active contours. We discuss active contours' limitations in the segmentation of immunohistochemical images and we demonstrate and motivate through extensive experiments the better accuracy of our fully automated approach compared to various active contours implementations.