In the current study, by integrating the analyses of lipidomics and proteomics, the compositional differences between colostrum and mature milk of Holstein cows were systematically investigated. We have identified a total of 1863 lipid metabolites and 1690 proteins. A small portion of them were highly differentiated between colostrum and mature milk. Among them, 23 highly differentiated lipid metabolites and 17 proteins were screened to run correlation analysis. The results showed that they are highly correlated; therefore, they could serve as biomarkers to distinguish colostrum from mature milk. Furthermore, among lipid metabolites, triacylglycerol (TG) (10:0_11:0_12:0) and sphingomyelin (SM) (20:0;2O/44:11) were identified as key regulatory molecules in glycerophospholipid metabolism and sphingomyelin metabolism. In proteins, cadherin 3 (CDH3) protein and alpha-S1-casein (CSN1S1) protein have been identified as potentially important characteristic proteins. In addition, the level of α-ketoglutarate (α-KG) in colostrum was two-fold lower than that in mature milk and its level strongly correlated with several differentiated metabolites and tricarboxylic acid (TCA) cycle-related proteins, including isocitrate dehydrogenase 1 (IDH1), aconitase 1 (ACO1), and dihydrolipoamide dehydrogenase (DLD). This indicates that α-KG is one of the most important differential molecules to determine the compositions of colostrum and mature milk. These findings provide molecular basis for understanding the nutritional value and the regulatory mechanisms related to the compositions of colostrum and mature milk.
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.