[Preliminary establishment of an unsupervised quantification model of Ki-67 proliferation index based on local variable threshold method].

PURPOSE: To develop an effective machine learning method for estimation of Ki-67 cell proliferation index. METHODS: Oral squamous cell carcinoma(OSCC) slices were selected for Ki-67 immunohistochemical staining. The digital pathology images were obtained through whole-slide imaging technology. Variable threshold method based on local statistics was applied to preprocess the images, aiming at reducing the noise in the images. Adaptive threshold method was used to remove the irrelevant light-colored background area in the image, retaining the nucleus part. A threshold method in space was applied to differentiate brown from blue content. Finally, the proliferation index was estimated and compared with manual and the color deconvolution method by paired sample t test and spearman correlation coefficients with SPSS 24.0 software package. RESULTS: A new nucleus detection and classification method was established, which can process pathologic images of different sizes, and effectively detect immunohistochemical brown positive cells and blue negative cells. There was no significant difference between this algorithm and manual counting（P＞0.05）, but the speed was faster. The calculation efficiency advantage was more obvious when processing a large image, and the detection result of Ki-67 proliferation index was better than the commonly used color deconvolution method（P＜0.05）. CONCLUSIONS: The automatic nucleus quantitative analysis method developed in this study can analyze Ki-67 staining of the nucleus in OSCC cells efficiently and calculate the proliferation index, which can be used for auxiliary diagnosis in pathology.

NF-κB: A novel therapeutic pathway for gastroesophageal reflux disease?

Although gastroesophageal reflux disease (GERD), a common chronic disease in clinical practice, has been widely studied, its potential adverse impact on patients is still a significant clinical concern. It is necessary to understand the pathogenesis of the disease and choose appropriate treatment according to its mechanism. The pathogenesis of GERD is diverse and complex. As the traditional treatment methods are expensive and ineffective in alleviating symptoms in some patients, new treatment options need to be explored. Our previous study suggested that the activation of nuclear factor-kappa beta (NF-κB) in esophageal mucosa may be related to the injury of epithelial barrier function caused by reflux. Based on the literature and our previous study results, it is speculated that inhibition of NF-κB activation may block the insult of GERD on the esophageal mucosal barrier. NF-κB may play an important role in the development of GERD. This article reviews the pathogenesis of GERD and the relationship between NF-κB and GERD, in order to provide new strategies for the treatment of GERD.

[Gene expression signature for lymphatic metastasis of human lung adenocarcinoma].

BACKGROUND AND OBJECTIVE: Distant metastasis is a major cause of mortality for patients with lung adenocarcinoma. So far, the mechanism of tumor metastasis is unknown. This study was to screen the gene expression signature in relation to lymphatic metastasis of human lung adenocarcinoma. METHODS: Primary lung adenocarcinoma tissues and regional lymph nodes were obtained from 22 patients underwent radical resection. The samples were classified into three groups: 11 cases of primary lung adenocarcinoma without lymphatic metastasis (TxN-), 11 cases of primary lung adenocarcinoma with lymphatic metastasis (TxN+), and 11 cases of the corresponding tumor cells from metastatic lymph nodes(N+). Total RNA was extracted from laser microdissected tumor samples. Adequate RNA starting materials from the primary tumors or metastatic nodes were labeled and then hybridized into the same microarray containing 6000 known human genes or expressed sequence tags (ESTs). After scanning, data analyses were performed using GeneSpring 6.2. RESULTS: Among 17 differentially expressed genes between the TxN+ and TxN-groups, 12 genes were significantly elevated and five genes were significantly downregulated in the TxN+ group compared with the TxN-group. There were 53 differentially regulated genes between the N+ and TxN+ groups, among which 25 genes were overexpressed and 28 genes were suppressed in the N+ group. CONCLUSION: The combination of early oncogenic alterations and later acquisition of a set of genetic alterations may determine the metastatic potential of lung adenocarcinoma.