Sequence-specific detection of double-stranded DNA (dsDNA) under physiological conditions remains challenging because the complementary strand is inaccessible to conventional oligonucleotide probes, often requiring thermal denaturation or protein-assisted strand separation. Here, we developed a binary DNAzyme (BiDz) sensor for sequence-specific dsDNA detection at 37 °C. While the all-DNA BiDz failed to recognize dsDNA efficiently, incorporating alternating locked nucleic acid (LNA)/DNA residues into the analyte-binding arms enabled efficient strand invasion and markedly improved signal generation. Integration of the optimized BiDz into a multivalent DNAzyme nanomachine (DNM) further enhanced target binding and reduced the detection limit for dsDNA amplicons to 25 pM, a 3.5-fold improvement over BiDz alone. The DNM also detected long plasmid dsDNA at nanomolar concentrations while maintaining excellent discrimination of centrally located single-base mismatches. Both BiDz and DNM demonstrated excellent discrimination of both A–C and the most challenging G–T mismatches. These findings demonstrate that combining alternating LNA/DNA-modified binding arms with a multivalent DNM architecture enables sensitive and highly specific dsDNA detection under physiological conditions, providing a promising platform for isothermal nucleic acid analysis.
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 seque...
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.