Alive anisakids cause acute gastrointestinal diseases, and dead worms contained in food can provoke sensibilization and allergic reactions in humans. Detected in the purchased minced salmon Oncorhynchus nerka nematodes were identified as Anisakis simplex sensu stricto (Anisakidae). We found that recently published phylogenetic trees (reconstructed using different ribosomal and mitochondrial genetic markers) showed independent clusterization of species recognized in the A. simplex sensu lato species complex. This prompted us to undertake this full-fledged molecular genetics study of anisakids from Kamchatka with phylogenetic reconstructions (NJ/ML) and calculated ranges of interspecific and intergeneric p-distances using ITS1-5.8S-ITS2 sequences. We confirmed that molecular markers based on the ITS region of rDNA were able to recognize 'pure' specimens belonging to the cryptic species. We offer new insights into the systematics of anisakids. The genus Anisakis sensu stricto should include Anisakis simplex sensu stricto, Anisakis pegreffii, Anisakis berlandi, Anisakis ziphidarum, and Anisakis nascettii. Presumably, two genera should be restored in the structure of the subfamily Anisakinae: Skrjabinisakis for the species Anisakis paggiae, Anisakis brevispiculata, and Anisakis physeteris; and Peritrachelius for the species Anisakis typica. In addition, we provide the short annotated list of some genera of the family Anisakidae, including their diagnoses.

The fractal formalism in combination with linear image analysis enables statistically significant description and classification of “irregular” (in terms of Euclidean geometry) shapes, such as, outlines of in vitro flattened cells. We developed an optimal model for classifying bivalve Spisula sachalinensis and Callista brevisiphonata immune cells, based on evaluating their linear and non-linear morphological features: size characteristics (area, perimeter), various parameters of cell bounding circle, convex hull, cell symmetry, roundness, and a number of fractal dimensions and lacunarities evaluating the spatial complexity of cells. Proposed classification model is based on Ward’s clustering method, loaded with highest multimodality index factors. This classification scheme groups cells into three morphological types, which can be distinguished both visually and by several linear and quasi-fractal parameters.

The fractal formalism in combination with linear image analysis enables statistically significant description and classification of “irregular” (in terms of Euclidean geometry) shapes, such as, outlines of in vitro flattened cells. We developed an optimal model for classifying bivalve Spisula sachalinensis and Callista brevisiphonata immune cells, based on evaluating their linear and non-linear morphological features: dimensional characteristics (area, perimeter), various parameters of cell bounding circle, convex hull, cell symmetry, roundness, and a number of fractal dimensions and lacunarities evaluating the spatial complexity of cells. Proposed classification model is based on Ward’s clustering method, loaded with highest multimodality index factors. This classification scheme groups cells into three morphological types, which can be distinguished both visually and by several linear and quasi-fractal parameters.

The fractal formalism in combination with linear image analysis enables statistically significant description and classification of “irregular” (in terms of Euclidean geometry) shapes, such as, outlines of in vitro flattened cells. We developed an optimal model for classifying bivalve Spisula sachalinensis and Callista brevisiphonata immune cells, based on evaluating their linear and non-linear morphological features: dimensional characteristics (area, perimeter), various parameters of cell bounding circle, convex hull, cell symmetry, roundness, and a number of fractal dimensions and lacunarities evaluating the spatial complexity of cells. Proposed classification model is based on Ward’s clustering method, loaded with highest multimodality index factors. This classification scheme groups cells into three morphological types, which can be distinguished both visually and by several linear and quasi-fractal parameters.