Urban beach evolution in Saint Louis, Senegal (West Africa) using shore-based camera video monitoring as a management tool - Amadou Diouf; Cheikh Omar Tidjani Cissé; Rafael Almar; Baba Sy; Boubou Aldiouma Sy; Adelaide Taveneau; Issa Sakho; Bamol Ali Sow; Grégoire Abessolo Ondoa; Abdoulaye Ndour; Kader Ba; Erwin W.J. Bergsma; et al. (Regional Studies in Marine Science, 2025)

Discrimination between hypervirulent and non-hypervirulent ribotypes of Clostridioides difficile by MALDI-TOF mass spectrometry and machine learning - Ahmed Mohamed Mostafa Abdrabou; Issa Sy; Markus Bischoff; Manuel J. Arroyo; Sören L. Becker; Alexander Mellmann; Lutz von Müller; Barbara Gärtner; Fabian K. Berger (European Journal of Clinical Microbiology & Infectious Diseases, 2023)
Hypervirulent ribotypes (HVRTs) of Clostridioides difficile such as ribotype (RT) 027 are epidemiologically important. This study evaluated whether MALDI-TOF can distinguish between strains of HVRTs and non-HVRTs commonly found in Europe. Obtained spectra of clinical C. difficile isolates (training set, 157 isolates) covering epidemiologically relevant HVRTs and non-HVRTs found in Europe were used as an input for different machine learning (ML) models. Another 83 isolates were used as a validation set. Direct comparison of MALDI-TOF spectra obtained from HVRTs and non-HVRTs did not allow to discriminate between these two groups, while using these spectra with certain ML models could differentiate HVRTs from non-HVRTs with an accuracy >95% and allowed for a sub-clustering of three HVRT subgroups (RT027/RT176, RT023, RT045/078/126/127). MALDI-TOF combined with ML represents a reliable tool for rapid identification of major European HVRTs.