Tunisian pemphigus is a newly described form of endemic pemphigus whose clinical, histological and epidemiological characteristics have recently been detailed. The objective of this study was to analyse the binding properties of autoantibodies present in sera from patients with endemic Tunisian pemphigus using immunoblotting and indirect immunoelectron microscopy (IEM). Thirty patients with pemphigus foliaceus (PF) and six with pemphigus vulgaris (PV) seen in the dermatology department of Tunis Hospital between 1992 and 1994 were selected for this study. Seven of 30 (23%) and six of 12 (50%) PF sera tested bound to the 160 kDa band of desmoglein 1 when tested on bovine tongue and human epidermal extracts, respectively. Two of six and two of three PV sera tested bound to the 130 kDa desmoglein 3 in these two extracts. Immunoblot and indirect IEM showed that 24 of 30 (80%) PF sera contained IgG1, IgG3 or IgG4 antibodies that bound to a 185-kDa polypeptide localized on the desmosomal plaque. This immunological analysis showed that most endemic Tunisian pemphigus sera correspond to PF sera and are characterized by a high frequency of autoantibodies directed against a recently identified 185-kDa antigen of the desmosomal plaque.
Over the last decades, large-scale conservation projects have emerged that require collecting ecological data over broad spatial and temporal coverage. Yet, obtaining relevant information about large-scale population dynamics from a single monitoring program is challenging, and often several sources of data, possibly heterogeneous, need to be integrated. In this context, spatial integrated models combine multiple data types into a single analysis to quantify population dynamics of a targeted population. Using available information at different spatial or temporal scales, spatial integrated models have the potential to produce detailed ecological estimates that would be difficult to obtain if data were analyzed separately. So far, these models are available for open populations to estimate demographic parameters (survival, recruitment), therefore requiring data collected in long-term monitoring programs. In conservation biology however, we often need to quantify population abundance and density in closed populations. In this paper, we showcase the implementation of spatial integrated models to closed populations in a conservation context. We analyzed spatial capture-recapture data together with distance-sampling data to estimate abundance and density. Focusing on the Mediterranean bottlenose dolphins (Tursiops truncatus) as a case study, we combined 21,464 km of photo-identification boat surveys collecting spatial capture-recapture data with 24,624 km of aerial line-transect following a distance-sampling protocol. We compared the performances of the spatial integrated model, with that of the distance sampling model, and the spatial capture-recapture model separated. We discussed the benefits of using a spatial integrated model in the context of the assessment of French Mediterranean bottlenose dolphin conservation status to inform continental scale public policies. Overall, we emphasize the usefulness of spatial integrated model to make the most of available datasets in a conservation context. Spatial integrated models are widely applicable and relevant to conservation research and biodiversity assessment at large spatial scales.
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