Comparing Deep Learning Models for Multi-cell Classification in Liquid- based Cervical Cytology Image.

Liquid-based cytology (LBC) is a reliable automated technique for the screening of Papanicolaou (Pap) smear data. It is an effective technique for collecting a majority of the cervical cells and aiding cytopathologists in locating abnormal cells. Most methods published in the research literature rely on accurate cell segmentation as a prior, which remains challenging due to a variety of factors, e.

Histopathology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.

Nonalcoholic fatty liver disease (NAFLD) is the liver injury most often associated with disorders of insulin resistance, including obesity, diabetes and the metabolic syndrome. The term encompasses several patterns of liver injury, including a relatively benign condition of steatosis without hepatocellular injury, nonalcoholic steatohepatitis (NASH), and a pattern of zone 1 steatosis, inflammation and fibrosis mainly observed in prepubertal children. Staging and grading systems have been developed to characterize the histological changes in NAFLD, mainly as a tool for clinical research.

Cutaneous metastasis of prostate cancer: a case report and review of the literature with bioinformatics analysis of multiple healthcare delivery networks.

Distant cutaneous metastases of prostate carcinomas are extremely rare, despite its high incidence and prevalence. Most cases are either a result of local extension, such as into seminal vesicles or distant metastases to bone. Few cases of true cutaneous metastatic prostate carcinoma exist in the literature.

Interferon-gamma inhibits T84 epithelial cell migration by redirecting transcytosis of beta1 integrin from the migrating leading edge.

Intestinal inflammation is associated with epithelial damage and formation of mucosal wounds. Epithelial cells migration is required for wound closure. In inflammatory status, migrating epithelial cells are exposed to proinflammatory cytokines such as IFN-gamma.