Toxicity assessment of airborne ultrafine particles: Role of transport emissions.

Airborne quasi-ultrafine particle samples were collected from different outdoor sites in Barcelona (NE Spain, 35 samples) and the Valencia subway (about 400 km south of Barcelona, 3 samples). Locations and schedules were designed to cover cold and warm seasons and to represent the impact of different types of transport (cars, trains, ships, and planes). Extracts from PTFE filters (methanol:dichloromethane 1:2) were used to test toxic effects in human cell lines (Induction of reactive oxygen species, inflammatory response) and in zebrafish embryos (expression of xenobiotic response-related genes, cyp1a1, gsa1 and hao1).

Concentrations and origins of ultrafine particles at a major European harbor.

The maritime transport sector poses significant air quality concerns, particularly in nearby cities. Ultrafine particles (UFP, diameter < 100 nm) are of particular concern due to their potential health impacts. This study measured particle number concentrations (PNC), size distributions (PNSD), and other pollutants including particulate matter (PM), nitrogen oxides (NO), black carbon (BC), sulfur dioxide (SO) and ozone (O), organic markers and trace elements at a major European harbor and an urban background (UB) location.

Combining Postural Sway Parameters and Machine Learning to Assess Biomechanical Risk Associated with Load-Lifting Activities.

: Long-term work-related musculoskeletal disorders are predominantly influenced by factors such as the duration, intensity, and repetitive nature of load lifting. Although traditional ergonomic assessment tools can be effective, they are often challenging and complex to apply due to the absence of a streamlined, standardized framework. Recently, integrating wearable sensors with artificial intelligence has emerged as a promising approach to effectively monitor and mitigate biomechanical risks.

Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review.

: Gait analysis, traditionally performed with lab-based optical motion capture systems, offers high accuracy but is costly and impractical for real-world use. Wearable technologies, especially inertial measurement units (IMUs), enable portable and accessible assessments outside the lab, though challenges with sensor placement, signal selection, and algorithm design can affect accuracy. This systematic review aims to bridge the benchmarking gap between IMU-based and traditional systems, validating the use of wearable inertial systems for gait analysis.