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Imbalance between MMPs and TIMPs may be involved in cancerization of oral lichen planus. MMP-2, MT1-MMP, and especially MMP-9 may be useful markers for judging potency of malignant transformation from oral lichen planus.

The correct conformation had lower MM/GBSA binding free energy in longer MD simulations for each FGFR1 inhibitor.

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Ghost cell odontogenic carcinoma (GCOC) is an exceptionally rare and malignant odontogenic tumor with aggressive growth characteristics. We describe a case of GCOC which was considerably derived from a previously resected calcifying cystic odontogenic tumor (CCOT). Cellular atypia, mitotic activity, Ki-67 labeling index and matrix metalloprotease-9 positive expression rate were all increased in the currently resected specimen compared to the initial one. This is a rare case of malignant transformation of CCOT to GCOC with respect to its histopathological and immunohistochemical findings.

Land subsidence risk assessment (LSRA) is a multi-attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor-level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster-Shafer (D-S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi-Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information--quantitative or qualitative, complete or incomplete, and precise or imprecise--to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.