Gait stability prediction through synthetic time-series and vision-based data.

Introduction: Gait stability assessment in older adults is challenged by limited data availability and measurement complexity, particularly among vulnerable populations and in limited resource settings. We address three research questions: (1) can synthetic data accurately replicate the statistical properties of gait parameters in older adults? (2) how effectively do synthetic data-trained models predict the Margin of Stability (MoS) when tested on real-world data? and (3) what specific biomechanical features contribute most significantly to the MoS predictions in older adults? To address these challenges, the present study proposes a novel approach to gait stability prediction by integrating computer vision with a data-centric synthetic data generation (SDG) approach using accessible, low-cost technology.

Methods: Using a public dataset from 14 healthy older adults (86.

A synthetic data-driven machine learning approach for athlete performance attenuation prediction.

Introduction: Athlete performance monitoring is effective for optimizing training strategies and preventing injuries. However, applying machine learning (ML) frameworks to this domain remains challenging due to data scarcity limitations. This study extends previous research by evaluating Tabular Variational Autoencoders (TVAE) for generating synthetic data to predict performance attenuation in Gaelic football athletes.

Real-Time PCR Quantification of Heteroplasmy in a Mouse Model with Mitochondrial DNA of C57BL/6 and NZB/BINJ Strains.

Mouse models are widely employed to study mitochondrial inheritance, which have implications to several human diseases caused by mutations in the mitochondrial genome (mtDNA). These mouse models take advantage of polymorphisms between the mtDNA of the NZB/BINJ and the mtDNA of common inbred laboratory (i.e.

Bacterial community associated with healthy and diseased reef coral Mussismilia hispida from eastern Brazil.

In order to characterize the bacterial community diversity associated to mucus of the coral Mussismilia hispida, four 16S rDNA libraries were constructed and 400 clones from each library were analyzed from two healthy colonies, one diseased colony and the surrounding water. Nine bacterial phyla were identified in healthy M. hispida, with a dominance of Proteobacteria, Actinobacteria, Acidobacteria, Lentisphaerae, and Nitrospira.

Induced gene expression in oyster Crassostrea gigas exposed to sewage.

Pacific oysters, Crassostrea gigas, were exposed to untreated sewage diluted in seawater. After 48h of exposure, the expression of genes associated to biotransformation pathways (CYP356A1, GSTO, MDR, FABP and ALAS) were analyzed in gills through semi-quantitative RT-PCR. A significant induction in all genes analyzed in the sewage-exposed oysters was observed.