Melanoma, also known as malignant melanoma, is a type of malignant tumour that originates from melanocytes in the basal layer of the epidermis. Primary malignant melanomas of the female genital tract are rare. Similarly, primary malignant melanoma of cervix, which originates from cervical melanocytes, is an extremely rare disease and the second most common type of female melanoma in women aged between 15 to 44 years worldwide. To date, primary malignant melanoma of the cervix is characterized by poor patient prognosis and little consensus exists regarding the best treatment therapy. The situation is worsened by lack of clinical studies with large samples. Notably, surgery remains the preferred treatment option for patients with primary malignant melanomas of the cervix. Current treatments are based on Federation International of Gynecology and Obstetrics(2018) staging with reference to National Comprehensive Cancer Network guidelines. This study is in order to find a more suitable treatment modality for primary malignant melanoma of cervix. Therefore, we first conducted an integrated analysis of case reports and series to assess the impact of various factors on the prognosis of such patients. In summary, this is the first pooled analysis including 149 cases of primary cervical melanoma. We found that patients who underwent radical hysterectomy-based surgery, those with non-metastatic lymph nodes and those who underwent lymphadenectomy had significantly higher survival rates. In patients who had RH-based surgery, survival rates at the 24m time point of those who did not add other treatments was higher than those who did, but for those who had total hysterectomy-based surgery, the addition of other treatments to prolong median survival may be considered. In the overall analysis, age and lymphadenectomy were associated with increased and reduced risk of death in these patients, respectively. Although there is no statistical difference, stage III&IV, TAH, lymphatic metastases increase the risk of death; whereas radical hysterectomy was associated with reduced risk of death. In the subgroup analysis, for patients who have undergone radical hysterectomy-based surgery, lymphadenectomy reduces the risk of death, while lymphatic metastases and complementary other treatments increase the risk of death. For patients who have undergone total hysterectomy-based surgery, complementary treatment reduces the risk of death. In conclusion, via summarizing previous reports, the recommended treatment procedure for PMMC are radical hysterectomy and lymphadenectomy. The addition of other treatment options for patients who undergoing RH-based surgery need further study.

The CO2 pneumoperitoneum could promote the proliferation and metastasis of human ovarian cancer in nude mice. This effect was positively correlated with the duration of CO2 pneumoperitoneum.

Among gynecological cancers, cervical cancer is a common malignancy and remains the leading cause of cancer-related death for women. However, the exact molecular pathogenesis of cervical cancer is not known. Hence, understanding the molecular mechanisms underlying cervical cancer pathogenesis will aid in the development of effective treatment modalities. In this research, we attempted to discern candidate biomarkers for cervical cancer by using multiple bioinformatics approaches. First, we performed differential expression analysis based on cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas database, then used differentially expressed genes for weighted gene co-expression network construction to find the most relevant gene module for cervical cancer. Next, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on the module genes, followed by using protein–protein interaction network analysis and Cytoscape to find the key gene. Finally, we validated the key gene by using multiple online sites and experimental methods. Through weighted gene co-expression network analysis, we found the turquoise module was the highest correlated module with cervical cancer diagnosis. The biological process of the module genes focused on cell proliferation, cell adhesion, and protein binding processes, while the Kyoto Encyclopedia of Genes and Genomes pathway of the module significantly enriched pathways related to cancer and cell circle. Among the module genes, SOX9 was identified as the hub gene, and its expression was associated with cervical cancer prognosis. We found the expression of SOX9 correlates with cancer-associated fibroblast immune infiltration in immune cells by Timer2.0. Furthermore, cancer-associated fibroblast infiltration is linked to cervical cancer patients’ prognosis. Compared to those in normal adjacent, immunohistochemical and real-time quantitative polymerase chain reaction (qPCR) showed that the protein and mRNA expression of SOX9 in cervical cancer were higher. Therefore, the SOX9 gene acts as an oncogene in cervical cancer, interactive with immune infiltration of cancer-associated fibroblasts, thereby affecting the prognosis of patients with cervical cancer.

Cervical cancer is one of the most common gynecologically malignancies worldwide. Although vaccine and cervical cancer screening including human papillomavirus testing, cytology testing, and colposcopy have developed rapidly in recent years, effectively reducing cervical cancer mortality, cervical cancer remains a malignancy with higher female fatality rates worldwide and has a high risk for socioeconomically disadvantaged groups. The combination of platinumpaclitaxel and chemotherapy, possibly with the addition of bevacizumab, is currently the treatment of choice for advanced cervical cancer, but it only has remission purposes. Therefore, new therapeutic strategies are needed for both locally advanced and metastatic cervical cancer. Here, we make a preliminary analysis of cervical cancer immunotherapy.

In the field of online learning, there is a problem of high student turnover rate. How to accurately identify learners and provide targeted teaching support services is an urgent problem for education researchers. In this paper, 1306 online learners majoring in finance from Shanghai Open University were selected as the subjects, and two kinds of data sets are adopted, which are learning data of online learning platform and learning behavior data of students based on xAPI, to analyze the relationship between learners' various online learning behaviors and learning achievements, and to determine the characteristics related to learning state of learners, describe the personalized learning state portrait, and select a variety of machine learning algorithms to build prediction model based on two data sets, to explore which data is more effective for building prediction models to identify potential risk learners. It is found that data mining analysis based on xAPI data has higher prediction accuracy than traditional online learning data.