Human papillomavirus and cervical cancer in the microbial world: exploring the vaginal microecology

The vaginal microbiota plays a crucial role in female reproductive health and is considered a biomarker for predicting disease outcomes and personalized testing. However, its relationship with human papillomavirus (HPV) infection and cervical cancer is not yet clear. Therefore, this article provides a review of the association between the vaginal microbiota, HPV infection, and cervical cancer. We discuss the composition of the vaginal microbiota, its dysbiosis, and its relationship with HPV infection, as well as potential mechanisms in the development of cervical cancer. In addition, we assess the feasibility of treatment strategies such as probiotics and vaginal microbiota transplantation to modulate the vaginal microbiota for the prevention and treatment of diseases related to HPV infection and cervical cancer. In the future, extensive replication studies are still needed to gain a deeper understanding of the complex relationship between the vaginal microbiota, HPV infection, and cervical cancer, and to clarify the role of the vaginal microbiota as a potential biomarker for predicting disease outcomes, thus providing a theoretical basis for personalized testing

Fuzzy random evaluation of creep model of frozen soft soil in metro tunnel construction using artificial ground freezing technique

Abstract Mastering the creep characteristics of artificial frozen soil and scientifically evaluating the creep model is an important guarantee for the safety of subway tunnel freezing construction. Base on the construction of Nantong metro tunnel, the uniaxial compressive strength tests of the artificially frozen soft soil were carried out to obtain the influence law of temperature on the uniaxial compressive strength, and the uniaxial creep tests were carried out to obtain the influence law of temperature and stress grade on creep, at − 5, − 10 and − 15 °C. The experimental results show that the creep characteristics of frozen soft soil specimens have obvious fuzzy randomness. The traditional ant colony algorithm is improved by optimizing the pheromone fuzzification coefficient, which improves the search efficiency and avoids the local optimum effectively. Subsequently, the improved fuzzy ant colony algorithm is used to invert the flexibility parameters of commonly used permafrost creep models. The fuzzy weight of evaluation index and the fuzzy random evaluation matrix were determined to evaluate the optimal creep model under three different stress levels of frozen soft soil. Finally, the reliability of the fuzzy random evaluation method was verified by engineering measured data