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Accurate, prompt, and reliable tools for the diagnosis of malaria are crucial for tracking the successes or drawbacks of control and elimination efforts, and for future programs aimed at global malaria eradication. Although microscopy remains the gold standard method, the number of imported malaria cases and the risk of reappearance of autochthonous cases stimulated several laboratories located in European countries to evaluate methods and algorithms suited to non-endemic settings, where skilled microscopists are not always available. In this review, an overview of the field evaluation and a comparison of the methods used for the diagnosis of malaria by European laboratories is reported, showing that the development of numerous innovations is continuous. In particular, the combination of rapid diagnostic tests and molecular assays with microscopy represents a reliable system for the early diagnosis of malaria in non-endemic settings.

Colistin resistance is one of the major threats for global public health, requiring reliable and rapid susceptibility testing methods. The aim of this study was the evaluation of a MALDI-TOF mass spectrometry (MS) peak-based assay to distinguish colistin resistant (colR) from susceptible (colS) Escherichia coli strains. To this end, a classifying algorithm model (CAM) was developed, testing three different algorithms: Genetic Algorithm (GA), Supervised Neural Network (SNN) and Quick Classifier (QC). Among them, the SNN- and GA-based CAMs showed the best performances: recognition capability (RC) of 100% each one, and cross validation (CV) of 97.62% and 100%, respectively. Even if both algorithms shared similar RC and CV values, the SNN-based CAM was the best performing one, correctly identifying 67/71 (94.4%) of the E. coli strains collected: in point of fact, it correctly identified the greatest number of colS strains (42/43; 97.7%), despite its lower ability in identifying the colR strains (15/18; 83.3%). In conclusion, although broth microdilution remains the gold standard method for testing colistin susceptibility, the CAM represents a useful tool to rapidly screen colR and colS strains in clinical practice.