A Gel-Free Budget-Friendly Approach to GFP-Tagged Viruses Quantification in Plant Samples

Abstract Viral diseases are an important threat to crop yield, as they are responsible for losses greater than US$30 billion annually. Thus, understanding the dynamics of virus propagation within plant cells is essential for devising effective control strategies. However, viruses are complex to propagate and quantify. Existing methodologies for viral quantification tend to be expensive and time-consuming. Here, we present a rapid cost-effective approach to quantify viral propagation using an engineered virus expressing a fluorescent reporter. Using a microplate reader, we measured viral protein levels and we validated our findings through comparison by western blot analysis of viral coat protein, the most common approach to quantify viral titer. Our proposed methodology provides a practical and accessible approach to studying virus-host interactions and could contribute to enhancing our understanding of plant virology

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m−2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m−2 (mean ≈ 350 g m−2), while predicted values ranged from 0 to ∼4000 g m−2 (mean ≈ 275 g m−2), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m−2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling

Participatory Strategies to Enhance Resilience and Job Satisfaction and Reduce Stress to Mitigate Early Retirement Intentions Among Nurses: Protocol for a Qualitative Study

Abstract Background: As Canada’s population ages, so does its workforce. Early retirement among nurses is on the rise and has become the norm within this workforce. It represents a major concern for maintaining an adequate and qualified workforce. On the one hand, the decision to take early retirement can be influenced by various factors, including occupational stress. By contrast, low job satisfaction can exacerbate early retirement intentions, while resilience is positively associated with the intention to remain at work. Little is known about how to mobilize these factors to promote healthy job retention for nurses as they age. Objective: This study aims to (1) explore the experiences of older nursing staff regarding their intention to take early retirement and the influence of occupational stress, resilience, and job satisfaction; (2) explore interventions used to optimize the influence of resilience and job satisfaction and minimize the influence of occupational stress on early retirement; and (3) generate and validate participatory strategies tailored to the context of older nursing staff to optimize the influence of resilience and job satisfaction and minimize the influence of occupational stress on early retirement. Methods: A 3-phase qualitative research design will be used. In phase 1, we will use an interpretive descriptive design using semistructured interviews to explore the experience surrounding early retirement intentions and related factors among nurses. In phase 2, we will use a scoping review to explore interventions used to optimize the influence of resilience and job satisfaction and minimize the influence of occupational stress on early retirement. In phase 3, we will use the technique for research of information by animation of a group of experts method with a group of 8 participants. This method will allow us to generate and validate participatory strategies tailored to the context of older nurses. Results: Initial results are expected in August 2025. The findings of this study will be shared through multiple platforms to maximize their reach and impact. This will include publishing scientific articles, completing a research dissertation, and presenting at conferences. A concise summary document highlighting key findings will be sent to study participants, who will also have the option to receive links to the online publications derived from the research. Conclusions: This protocol presents detailed information about the entire structure of the 3-phase research project. Studying early retirement issues among older nurses is essential. It promotes their health, retention, and inclusion, and recognizes their contributions to the sector. International Registered Report Identifier (IRRID): PRR1-10.2196/7208

Can a Recovery College be implemented online? Multi-perspective case study documenting the process of adapting courses online

Abstract Purpose This study aims to document the process of adapting Recovery College (RC) courses into an online format and assess whether online adaptation meets learners’ goals. The study describes the challenges encountered, the strategies deployed and the factors influencing implementation from the perspectives of four interested parties: coordination team, partners advisory committee, trainers and learners. Design/methodology/approach The study adopts a descriptive single-case study design. Several sources of data were collected: focus groups, implementation daybook, meeting minutes, interviews and satisfaction survey. Simple descriptive content analysis was used for all qualitative data, and simple descriptive statistical analyses were used for the online satisfaction survey with learners. Findings The results highlight challenges and strategies for adapting content and facilitation, as well as challenges and strategies for respecting RC key principles. Internal, organizational and technological factors have influenced the implementation. Most learners were satisfied with the courses attended and felt that it met their goals. Three overarching aspects of online implementation are discussed based on findings: training and supporting trainers, facilitation and pedagogical methods and ongoing monitoring and feedback to interested parties. Research limitations/implications Findings encourage further research to determine the extent to which online RC courses align with recommended strategies for reducing digital inequalities and implementing digital health interventions. Originality/value Few studies have focused on implementing RC online. This case study offers insights for organizations pursuing similar initiatives