East Asian Passiflora virus (EAPV) is a significant viral pathogen prevalent across passionfruit cultivation regions in China and causes substantial economic losses to the passionfruit industry. The development of a sensitive, rapid, and accurate diagnostic method is essential for virus identification and epidemiological surveillance to support effective disease management strategies. In this study, a SYBR Green-based real-time quantitative PCR (qPCR) assay was developed for EAPV detection using a specific primer set targeting the viral coat protein (CP) gene. The assay was optimized with a primer concentration of 0.2 μmol/L and an annealing temperature of 60°C. The primers exhibited high specificity, generating a standard curve with an amplification efficiency of 90.9% and a coefficient of determination (R2) of 0.992. The limit of detection was 11.41 × 102 copies/μL, representing a 1000-fold greater sensitivity than conventional PCR. Moreover, viral accumulation was successfully detected in both inoculated and systemic leaves of passionfruit plants. In 2025, a total of 120 suspected virus-infected passionfruit samples were collected from Yunnan Province, China, and all samples tested positive for EAPV using the developed qPCR assay. Overall, the SYBR Green-based qPCR method established in this study demonstrated high specificity and sensitivity, providing a reliable tool for rapid EAPV diagnosis and epidemiological investigations.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.