Towards a strategy for the conservation of the freshwater pearl mussel Margaritifera margaritifera in County Donegal, Ireland

This study attempts to identify the habitat requirements of the pearl mussel Margaritifea margaritifera in County Donegal, in north west Ireland, an area with little urban, industrial or intensive agricultural development. No mussels occur in rivers where calcium and conductivity levels are high or where the substratum is predominantly bedrock or fine sediment but it was not possible to distinguish clearly between mussel and non-mussel sites on the basis of ordination analysis. However, rivers which still support mussels and rivers with historical records of mussels are loosely grouped. Rivers which formerly supported mussels but lack living M. margaritifera appear to have suitable habitat for mussels; pearl fishing is the most likely reason for the extinction of these mussel populations. Where population densities are high, for example in locations on the rivers Eske, Clady and Owenea, conservation may necessitate the establishment of reserves. The prospect for the successful reintroduction of mussels into former mussel rivers such as the Finn and Eany Water, where suitable habitat exists and water quality is high, is very good.

Robust automated tumour segmentation on histological and immunohistochemical tissue images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.