Abstract
Free-floating sharedmicromobility services have been present in cities all around the world, however little is still known about the interaction between shared e-bikes and e-scooters. In the last few years shared e-scooters have experienced rapid growth worldwide, which, in some cities, jeopardizes the usage of shared e-bike services. Thus, this research work aims to explore if free-floating shared e-bikes can disrupt the usage of established e-scooter services. Acase study in the city of Braga, north of Portugal, is developed from September of 2022 until May of 2023 in order to allow the comparison and contrast of the trips made by each micromobility mode, travel time, main origin and destinations of trips, as well as trip characteristics (e.g., vehicle rotation, the total number of trips per micromobility mode, total distance traveled). Results showthat shared e-bikes and e-scooters are only used within city boundaries, and most of the trips originated in the parish where population density is higher. In Braga, riders prefer e-scooters when using a shared micro vehicle, since more than 98% of the trips made in the period studied weremade by this mode. Also, shared e-scooters traveled more than 260,000 km in these nine months, while only 2,400 km were traveled in e-bikes. In short, Braga has experienced a rapid establishment of shared e-scooters instead of shared e-bikes, it can be due to the fact that trips on e-scooters are seen to be fun, pleasant, and quicker by riders.

Abstract

Abstract
Background: Aberrant or loss of cell adhesion drives invasion and metastasis, key hallmarks of cancer progression. In this work, we hypothesized that a gene signature related to cell adhesion could predict breast cancer prognosis. Methods: Highly variant genes were tested for association with overall survival using Cox regression. Adhesion-related genes were identified through gene ontology analysis and multivariate Cox regression, with AIC selection, defined the prognostic signature. The AdhesionScore was then calculated as a weighted sum of gene expression, with risk stratification assessed by Kaplan–Meier and log-rank tests. Results: We found that the AdhesionScore was a significant independent predictor of poor survival in three large independent datasets, as it provided a robust stratification of patient prognosis in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (HR: 2.65; 95% CI: 2.33–3.0, p = 2.34 × 10-51), The Cancer Genome Atlas (TCGA) (HR: 3.46; 95% CI: 2.35–5.09, p = 3.50 × 10-10), and the GSE96058 (HR: 2.83; 95% CI: 2.20–3.65, p = 6.29 × 10-16) datasets. The 5-year risk of death in the high-risk group was 32.41% for METABRIC, 27.8% for TCGA, and 17.54% for GSE96058 datasets. Consistently, HER2-enriched and triple-negative breast carcinomas (TNBC) cases showed higher AdhesionScores than luminal subtypes, indicating an association with aggressive tumor biology. Conclusions: We have developed, for the first time, a molecular signature based on cell adhesion, as well as an associated AdhesionScore that can predict patient prognosis in invasive breast cancer, with potential clinical application. We developed a novel adhesion-based molecular signature, the AdhesionScore, that robustly predicts prognosis in breast cancer across independent cohorts, highlighting its potential clinical utility for patient risk stratification.