The purpose of this cross-sectional study was to identify the current awareness about cervical cancer prevention among rural women in Luohe City as well as its potential influencing factors. Meanwhile, these data were expected to provide a theoretical basis for Luohe future cervical cancer prevention and therapy. Based on geographical distribution, 40 villages in Luohe City were randomly selected, and questionnaires were given to women in each village. In this study, a total of 4665 questionnaires were distributed, and 4561 valid questionnaires were returned, with a recovery rate of 97.98%. The average score was 4.06 ± 2.46 out of 10. It was found that women had a high awareness rate of cervical cancer screening (55.25%) but a low awareness rate of human papillomavirus (HPV) and HPV vaccine (10.17%). Moreover, univariate and multivariable analyses showed that age > 45 years, low household income, low education level, being a farmer, spouse unemployment, no pregnancy or birth delivery history, no family or personal history of cervical disease, and no previous complimentary 2-cancer screening (i.e., breast cancer and cervical cancer) were all factors influencing the cognitive level of rural women in Luohe City (P < .05). However, ethnicity, marital status, and spouse education level were not correlated with cognitive level (P > .05). In conclusion, low awareness of cervical cancer prevention among rural women in Luohe was correlated with individual, family, and social factors. So it was recommended to cultivate the rural population knowledge, optimize screening strategies, and conduct targeted cervical cancer prevention and treatment in rural regions.

A tipping point signals the shift from a stable phase to a malignant state in cervical cancer progression. Identifying this transition is essential for early intervention, yet traditional biomarkers based on differential expression or undirected network measures often fail to capture it. Here, we introduce Causality-Directed Network Flow Entropy (CDNFE), a framework that quantifies entropy dynamics in directed regulatory networks to detect disease tipping points with superior sensitivity over expression-based methods. Applied to cervical cancer data which were derived from samples of different clinical stages collected from Luohe Central Hospital (single-cell, bulk transcriptome, simulations, and spatial transcriptomics), CDNFE consistently identified a precancerous tipping point and uncovered a biomarker module enriched for non-differentially expressed "dark genes." Within this module, FNDC3B and NECTIN4 emerged as central hubs, validated across multiple levels: (1) functionally essential in cervical cancer cell lines, (2) structurally important as driver nodes within regulatory networks, (3) mechanistically suggesting a potential link to PI3K/AKT signaling driven by epithelial-mesenchymal transition, and (4) spatially enriched in tumor regions in independent spatial transcriptomics sections. These findings establish CDNFE as a robust systems-level framework for tipping point detection and highlight FNDC3B and NECTIN4 as representative dark gene regulators of cervical cancer progression.