Oct 2026· DOAJ (DOAJ: Directory of Open Access Journals)
Alcohol Consumption and Health Effects
Abstract
Objective To investigate the effects of disulfiram (DSF) on the proliferation, apoptosis and gefitinib sensitivity of non-small cell lung cancer H1975 cells. Methods H1975 cells were cultured in vitro and treated with different concentrations of disulfiram for 24, 48, and 72 hours. The CCK-8 assay was used to assess the impact of disulfiram on cell proliferation, and appropriate concentrations were selected for subsequent experiments. Cells were treated with varying concentrations of gefitinib alone or in combination with disulfiram for 48 hours, and the half-maximal inhibitory concentration (IC50) was calculated to determine the reversal fold. Cells were treated with gefitinib, disulfiram and N-acetylcysteine alone or in combination for 48 hours. Apoptosis was detected by flow cytometry, intracellular reactive oxygen species levels were measured using the DCFH-DA method, and Western blotting was performed to assess the expression of stemness-related markers (ALDH1A1, SOX2), pathway-related markers (p-STAT3, STAT3), and apoptosis-related markers (Bax, Bcl-2). Results Disulfiram significantly inhibited H1975 cell proliferation in a concentration-dependent (0-10 μmol/L) and time-dependent (24-72 hours) manner (P<0.05). The IC50 of gefitinib alone was 11.13 μmol/L, which decreased to 4.148 μmol/L when combined with 1 μmol/L disulfiram, indicating that disulfiram effectively reversed gefitinib resistance by 2.68 times. Disulfiram significantly suppressed the upregulation of stem cell-related proteins SOX2 and ALDH1A1 induced by gefitinib (P<0.05), and this effect was partially counteracted by the reactive oxygen species inhibitor N-acetylcysteine. Compared to gefitinib and disulfiram monotherapy groups, the combination therapy group exhibited significantly increased apoptosis rates, elevated reactive oxygen species levels and pro-apoptotic Bax expression, and reduced p-STAT3 and anti-apoptotic Bcl-2 expression (P<0.05). Further clearance of reactive oxygen species with N-acetylcysteine reversed disulfiram′s inhibitory effect on the STAT3 pathway(P<0.05). Conclusions Disulfiram may enhance gefitinib sensitivity by upregulating reactive oxygen species levels and inhibiting the STAT3 signaling pathway.
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.