The detection of soluble amyloid-β (Aβ), the most neurotoxic species in early Alzheimer's disease (AD), remains a major analytical challenge. Conventional probes are designed to target the β-sheet structures of mature fibrils and are thus blind to these transient, nonfibrillar species. Here, we introduce "site-ordered engineering" strategy, a peptide-conjugated QMFluors conjugate designed to selectively target Aβ1-42 monomers with high fidelity. We identified the conjugation site order on the fluorophore as the key parameter controlling this molecular topology and self-assembly behavior. This breakthrough is enabled by a hydrogen-bond-driven recognition mechanism, fundamentally departing from classical dyes that target the β-sheets of mature fibrils. This yields an unprecedented "inverted selectivity" with a 20-fold fluorescence enhancement for monomers over fibrils. Using probe N-QM-KLVFF with super-resolution microscopy, we reveal the nanoscale "core-shell" biophysical phase diagram of plaques, visualizing dense fibrillar cores surrounded by monomeric/oligomeric halos. Furthermore, the probe demonstrates a limit of detection of pg/mL level and excellent linearity, meeting the stringent requirements for trace cerebrospinal-fluid-biomarker analysis. This work provides not only a powerful tool for early diagnosis and pathological investigation, but also establishes "aggregation-regulated accessibility" as a generalizable principle for designing probes for other dynamic amyloid protein targets.
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.