Plasma microRNAs are considered to be potential diagnostic biomarkers for endometriosis. Increasing evidence has shown that a huge amount of miRNAs are abnormally expressed in endometriosis plasma and play irreplaceable roles in diagnosis. The aim of the our study was to identify the differential expression of circular miRNA by reviewing the PubMed, ScienceDirect, and Cochrane databases between normal women and women with endometriosis and analyzing the miRNA data downloaded from the GEO database. Because of the differential miRNA expression in this review, we evaluated the diagnostic values of the differentially expressed miRNAs, particularly during the menstrual phases. According to the cut-off criteria with |log 2 FC|>1.0 and P < 0.05, 36 differentially expressed miRNAs were identified, including 13 upregulated miRNAs and 23 downregulated miRNAs. We developed miR-155, miR-574, miR-23a, and miR-520d via a Venn diagram. Functional enrichment analysis considered that the target miRNAs might be involved in various pathways related to endometriosis, including neurotrophin, Hippo, oocyte meiosis, ubiquitin mediated proteolysis, HTLV-Infection, FoxO, and Rap1 signaling pathways. CTNNB1, MYC, and ES R1 of transcription factors were related to the differentially expressed miRNAs. In summary, our study suggested that a four-miRNA could be included as a prognostic marker in endometriosis.

Coseismic landslides pose significant threats, causing widespread destruction of buildings, roads, pipelines, and leading to numerous casualties. In recent years, the frequency of earthquakes has increased, prompting a growing interest in regional-scale assessment techniques for coseismic landslides. The infinite slope model proposed by Newmark is widely used to evaluate coseismic landslide hazard. However, the infinite slope model fails to reflect the impact of rock mass structure on the stability of slopes. This paper proposes a novel approach for mapping the hazards of coseismic landslides by considering the roughness of the potential slide surfaces in the inner slope. The proposed method is validated using data from the 2013 Lushan earthquake. The datasets, including geological units, peak ground acceleration (PGA), and high-resolution digital elevation models of topography, are rasterized at a grid spacing of 30 meters. They are then combined within an infinite slope model based on Newmark permanent-deformation analysis, enabling the estimation of coseismic landslide displacement in each grid area resulting from the Lushan earthquake. The modeled displacements are compared with the inventory of landslides triggered by the Lushan earthquake, allowing the derivation of a confidence level function that relates predicted displacement to the spatial variation of coseismic landslides. Ultimately, a hazard map of coseismic landslides is generated based on the established confidence level function. This map serves as a valuable tool for predicting the hazard zone of seismic regions and offers essential insights for decision-making related to infrastructure development and post-earthquake construction.