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Our study aims at evaluating clinical predictors of menstrual cycle disorders in female athletes who compete in running disciplines. This is a prospective observational study. Women were recruited between January and May 2022. 53 patients were enrolled and completed a questionnaire about menstrual cycle, physical activity and food habits characteristics. 39,6% of women in our population had menstrual irregularities and reported a significantly higher number of kilometres run per week (67 vs 35, p:0.02). The number of kilometres run per week was associated with menstrual irregularities (for 10 km, OR 1,35; IC95% 1,05-1,73; p: 0,02) after adjusting for BMI, age, level of sport and caloric intake. The variable of “km run per week” appeared as a diagnostic indicator of irregular menstrual cycle with statistical significance (AUC ROC curve 0,71, IC95% 0,54-0,86, p-value = 0,01) and the cut off-of 65 km run per week is a good indicator of the presence of irregular menstrual cycle (sensitivity (SE) and specificity (SP) of 55% and 81,48%). Menstrual cycle disorders are very frequent in female athletes and the variable of km run per week may have a role in screening endurance athletes at high risk for them.

The EC directive REACH (EC1907/2006) sets, amongst others, the need for all the chemicals to be tested for their carcinogenic potential. In vitro assays can provide a fast and reliable tool for screening purposes. The Cell Transformation Assay (CTA) is one of the in vitro assays in the most advanced phase of the validation process and the only one able to evaluate both the genotoxic and the non-genotoxic potentials. The evaluation of results of the CTA is based on the scoring of transformed colonies (foci) by a trained expert on the basis of their morphological features. Levels of cell packing and multilayered growth, as well as fibroblastic shape of cells, criss-crossing and invasion of the surrounding monolayer features are evaluated for classification. While the decision making process is based on standard criteria, their interpretation is potentially biased, especially in borderline cases, due to a certain degree of subjectivism inherent in the evaluation of qualitative features. This aspect is critical towards the international validation of the CTA assay: subjectivity driven error might in fact result in under or over estimation of the carcinogenic potential of tested compounds. In this work, different approaches were used to develop an objective method to give decisional support to the operator in the classification procedure. Biological markers related to the transformation process (p53, cx43), and to a general cell stress (Hsp70) were analyzed. A novel technique for the in focus localization of biological markers of transformation was developed. RNA whole genome screening was used to set the conditions for future molecular characterization of foci-derived cell lines. A novel, Quantitative Index of Dissimilarity has been obtained by statistical descriptors capturing morphological features and employing an unsupervised image analysis approach, in order to help the operator in the decisional process of scoring the borderline cases.

The human carcinogenicity evaluation of chemicals has a great impact on public health. In vitro methods, such as the cell transformation assay (CTA), allow for a fast and reliable assessment of the carcinogenic potential of a chemical compound in comparison with the standard two-year bioassay. The scoring and classification of foci in selected cell lines is performed, after staining, by light microscopy. Foci can be separated into three classes: type I, which are scored as non-transformed, and types II and III that are considered to include fully transformed foci. However, in a number of cases, even an expert is uncertain about the attribution of a focus to a given class, due to its mixed or intermediate nature. Here, we suggest a simple approach to classifying mixed or intermediate foci by exploiting the quantitative information available from images, which is captured by statistical descriptors. A quantitative index is proposed, to describe the degree of dissimilarity of mixed and intermediate images to the three well-distinguished classes

The Cell Transformation Assay (CTA) is one of the promising in vitro methods used to predict human carcinogenicity. The neoplastic phenotype is monitored in suitable cells by the formation of foci and observed by light microscopy after staining. Foci exhibit three types of morphological alterations: Type I, characterized by partially transformed cells, and Types II and III considered to have undergone neoplastic transformation. Foci recognition and scoring have always been carried visually by a trained human expert. In order to automatically classify foci images one needs to implement some image understanding algorithm. Herewith, two such algorithms are described and compared by performance. The supervised classifier (as described in previous articles) relies on principal components analysis embedded in a training feedback loop to process the morphological descriptors extracted by "spectrum enhancement" (SE). The unsupervised classifier architecture is based on the "partitioning around medoids" and is applied to image descriptors taken from histogram moments (HM). Preliminary results suggest the inadequacy of the HMs as image descriptors as compared to those from SE. A justification derived from elementary arguments of real analysis is provided in the Appendix