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Chen Wang

Publications and source records attributed to Chen Wang.

3 recordsLinked to original sources
PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗
PubMed2026

Role of nicotine metabolite ratio in pharmacological interventions on smoking cessation: A systematic review and meta-analyses of randomized controlled trials.

BACKGROUND AND OBJECTIVES: Emerging evidence suggests that the nicotine metabolite ratio (NMR) may influence the efficacy of smoking cessation, yet its role across pharmacotherapies remains unclear. This study aims to investigate how NMR affects cessation outcomes under different medications to guide personalized treatment. METHODS: We searched PubMed, Medline, EMBASE, and the Cochrane Central Register of Controlled Trials (inception to September 30, 2024) for randomized controlled trials on pharmacotherapy for smoking cessation with NMR data. Data were synthesized using random-effects models, with heterogeneity assessment. The primary outcome was verified smoking cessation rate at the end of treatment or the closest time-point. RESULTS: Eleven RCTs with accessible full text were included in the qualitative analyses and nine were included in the quantitative synthesis. For non-titratable nicotine replacement therapy (NRT), normal/fast metabolizers demonstrated lower odds of smoking cessation than slow metabolizers (Odds Ratio, OR=0.81, 95% confidence interval, CI=0.68-0.96; 5 studies, I²=62.5%). No significant associations were shown between normal/fast and slow metabolizers using titratable NRT (OR=1.04, 95% CI=0.95-1.14; 2 studies, I²=0%), bupropion (OR=0.67, 95% CI=0.38-1.16; 2 studies, I²=51.4%), or varenicline (OR=1.17, 95% CI=0.79-1.74; 4 studies, I²=59.8%). CONCLUSION: Current evidence demonstrates that NMR moderates' treatment efficacy among those who smoke using non-titratable NRT, with slow metabolizers achieving significantly better cessation outcomes than normal/fast metabolizers. Substantial further research is needed to determine optimal medication hierarchies across metabolic profiles.

Humans↗
PubMed2026

ZrO₂@C-based colorimetric/photothermal dual-mode immunosensor coupled with a novel monoclonal antibody for quantification of Aspergillus ochraceus biomass.

Aspergillus ochraceus contaminates agricultural products and produces nephrotoxic, carcinogenic ochratoxin A (OTA), posing severe food safety hazards. A dual-signal lateral flow immunochromatographic assay (dLFIA) based on ZrO₂@C nanoprobes was established for quantitative detection of A. ochraceus biomass. A novel monoclonal antibody (mAb 4B4) was prepared as the capture antibody to immobilize A. ochraceus mycelial lysate antigen on the test line, and a rabbit polyclonal antibody (pAb G2801) as the detection antibody to modify ZrO₂@C composites (synthesized via UiO-66 pyrolysis) into 200 nm colorimetric/photothermal nanoprobes. This dLFIA achieved limits of detection of 0.164 μg/mL (colorimetric) and 0.517 μg/mL (photothermal). This efficient and reliable method allows quantitative analysis of A. ochraceus biomass, which is suitable for routine monitoring of fungal contamination in agro-food matrices.

Antibodies, Monoclonal↗