Video-based assessment of cyclist-tram track interactions in wet road conditions

Cyclist underreporting of lower severity and single cyclist collisions to police results in the underestimation of the societal costs of lower severity and single cyclist collisions [1], [2]. Prevention strategies for these types of collisions are becoming a popular area of research, and video-based approaches have obvious potential for these cases, allowing for detailed analyses of underreported lower severity and single cyclist falls. Video-based studies have been used to investigate site-specific cyclist safety issues such as railway crossings [3 ]. They have also been used for near-collision or near-miss incidents and Surrogate Measures of Safety (SMoS), e.g., [4]. A recent Irish study has identified the most common collision configurations and factors with the inclusion of unreported cases [5]. Findings indicate that falls involving interactions with light rail tram tracks are common in Dublin; they were the most common infrastructural collision partner in this study and a contributing factor in 23% of single cyclist collisions (ibid.), supplementing international findings [6], [7]. Furthermore, along with increasing popularity of cycling, many new light rail systems are being implemented across Europe as part of a broader move towards sustainable transport [8]. Accordingly, further investigation is required to avoid potential conflicts. Therefore, this study aims to use video-based assessment to correlate fall risk with trajectories and crossing angles. [From: Introductiojn

Video-based assessment of cyclist-tram track interactions in wet road conditions

Cyclist underreporting of lower severity and single cyclist collisions to police results in the underestimation of the societal costs of lower severity and single cyclist collisions [1], [2]. Prevention strategies for these types of collisions are becoming a popular area of research, and video-based approaches have obvious potential for these cases, allowing for detailed analyses of underreported lower severity and single cyclist falls. Video-based studies have been used to investigate site-specific cyclist safety issues such as railway crossings [3 ]. They have also been used for near-collision or near-miss incidents and Surrogate Measures of Safety (SMoS), e.g., [4]. A recent Irish study has identified the most common collision configurations and factors with the inclusion of unreported cases [5]. Findings indicate that falls involving interactions with light rail tram tracks are common in Dublin; they were the most common infrastructural collision partner in this study and a contributing factor in 23% of single cyclist collisions (ibid.), supplementing international findings [6], [7]. Furthermore, along with increasing popularity of cycling, many new light rail systems are being implemented across Europe as part of a broader move towards sustainable transport [8]. Accordingly, further investigation is required to avoid potential conflicts. Therefore, this study aims to use video-based assessment to correlate fall risk with trajectories and crossing angles. [From: Introductiojn

Video-based assessment of cyclist-tram track interactions in wet road conditions

Cyclist underreporting of lower severity and single cyclist collisions to police results in the underestimation of the societal costs of lower severity and single cyclist collisions [1], [2]. Prevention strategies for these types of collisions are becoming a popular area of research, and video-based approaches have obvious potential for these cases, allowing for detailed analyses of underreported lower severity and single cyclist falls. Video-based studies have been used to investigate site-specific cyclist safety issues such as railway crossings [3 ]. They have also been used for near-collision or near-miss incidents and Surrogate Measures of Safety (SMoS), e.g., [4]. A recent Irish study has identified the most common collision configurations and factors with the inclusion of unreported cases [5]. Findings indicate that falls involving interactions with light rail tram tracks are common in Dublin; they were the most common infrastructural collision partner in this study and a contributing factor in 23% of single cyclist collisions (ibid.), supplementing international findings [6], [7]. Furthermore, along with increasing popularity of cycling, many new light rail systems are being implemented across Europe as part of a broader move towards sustainable transport [8]. Accordingly, further investigation is required to avoid potential conflicts. Therefore, this study aims to use video-based assessment to correlate fall risk with trajectories and crossing angles. [From: Introductiojn

Dishevelled limits Notch signalling through inhibition of CSL

Notch and Wnt are highly conserved signalling pathways that are used repeatedly throughout animal development to generate a diverse array of cell types. However, they often have opposing effects on cell-fate decisions with each pathway promoting an alternate outcome. Commonly, a cell receiving both signals exhibits only Wnt pathway activity. This suggests that Wnt inhibits Notch activity to promote a Wnt-ON/Notch-OFF output; but what might underpin this Notch regulation is not understood. Here, we show that Wnt acts via Dishevelled to inhibit Notch signalling, and that this crosstalk regulates cell-fate specification in vivo during Xenopus development. Mechanistically, Dishevelled binds and directly inhibits CSL transcription factors downstream of Notch receptors, reducing their activity. Furthermore, our data suggest that this crosstalk mechanism is conserved between vertebrate and invertebrate homologues. Thus, we identify a dual function for Dishevelled as an inhibitor of Notch signalling and an activator of the Wnt pathway that sharpens the distinction between opposing Wnt and Notch responses, allowing for robust cell-fate decisions

LuNER: Multiplexed SARS-CoV-2 detection in clinical swab and wastewater samples

Clinical and surveillance testing for the SARS-CoV-2 virus relies overwhelmingly on RT-qPCR-based diagnostics, yet several popular assays require 2-3 separate reactions or rely on detection of a single viral target, which adds significant time, cost, and risk of false-negative results. Furthermore, multiplexed RT-qPCR tests that detect at least two SARS-CoV-2 genes in a single reaction are typically not affordable for large scale clinical surveillance or adaptable to multiple PCR machines and plate layouts. We developed a RT-qPCR assay using the Luna Probe Universal One-Step RT-qPCR master mix with publicly available primers and probes to detect SARS-CoV-2 N gene, E gene, and human RNase P (LuNER) to address these shortcomings and meet the testing demands of a university campus and the local community. This cost-effective test is compatible with BioRad or Applied Biosystems qPCR machines, in 96 and 384-well formats, with or without sample pooling, and has a detection sensitivity suitable for both clinical reporting and wastewater surveillance efforts