In this work, a laser-induced fluorescence (LIF) detection system built in a modular assembling mode was developed based on commercial LEGO blocks and 3D printed blocks. We designed and fabricated a variety of 3D printed building blocks fixed with optical components, including laser light source, filters, lens, dichroic mirror, photodiode detector, and control circuits. Utilizing the relatively high positioning precision of the plug-in blocks, a modular construction strategy was adopted using the flexible plug-in combination of the blocks to build a highly sensitive laser-induced fluorescence detection system, LIFGO.
View Article and Find Full Text PDFObjective: To explore the outcomes of oncology, fertility, and pregnancy in patients after undergoing neoadjuvant chemotherapy (NACT) followed by fertility-sparing operations with cervical cancer, and its value in clinical treatment.
Materials And Methods: A total of 11 patients from seven hospitals in Beijing with cervical cancer since August 2009 to December 2011, who had undergone fertility- sparing treatments were recruited in this study.
Results: Among the 11 patients, there were nine cases of squamous cell carcinoma, two cases of adenocarcinoma, one case in Stage IA2, and ten cases in Stage IB1 (FIGO, 2009).
Objective: To clarify the relationship between the expression of dual specificity phosphatase-1 (DUSP1) and the prognosis of endometrioid adenocarcinoma.
Methods: The expression of DUSP1 was determined by immunohistochemical staining in specimens from 81 patients with endometrial carcinoma undergoing surgical resection. The relationship between DUSP1 expression, clinicopathological factors and prognosis were further evaluated.
Background: Early stage (FIGO stage I-II) endometrioid endometrial adenocarcinoma (EEA) is very common in clinical practice. However, patients with the early stage EEA show various clinical behaviors due to biological heterogeneity. Hence, we aimed to discover distinct classes of tumors based on gene expression profiling, and analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters.
View Article and Find Full Text PDFObjective: To explore the impact of 2009 International Federation of Gynecology and Obstetrics (FIGO) staging system alteration for stage I endometrioid adenocarcinoma on its' prognosis assessing.
Methods: A retrospective study was carried out on 244 cases with endometrial carcinoma admitted in Peking University People's Hospital from Jan.1995 to Feb.
Beijing Da Xue Xue Bao Yi Xue Ban
October 2011
Objective: To explore the relationships between the expressions of estrogen receptor (ER), progestin receptor (PR), phosphatase and tension homology deleted on chromosome ten (PTEN), p53, Ki-67 and the clinicopathologic features and prognosis in endometrial carcinoma.
Methods: The data of clinical characteristics, pathological types, histological grades, follow-ups and the expressions of molecular markers detected by immunohistochemistry, and collected from 200 patients with primary endometrial carcinoma, were analyzed.
Results: (1) In the cases of endometrial carcinoma, the expression rates of ER, PR, PTEN, p53 were 86.
Objective: To explore the lymph nodes (LN) metastasis characters of the endometrial carcinoma and its relation with the patients' prognosis.
Methods: A retrospective study was carried out on 227 cases of endometrial carcinoma who admitted to our department and underwent LN excision from Jul.2000 to Feb.
Objective: Recently, a high frequency of mutations in mitochondrial DNA (mtDNA) has been detected in ovarian cancer. To explore the alterations of proteins in mitochondria in ovarian cancer, a pair of human ovarian carcinoma cell lines (SKOV3/SKOV3.ip1) with different metastatic potentials was examined.
View Article and Find Full Text PDFObjective: To investigate whether the molecular classification of endometrial cancer based on gene expression profiles can predict the biological behavior of the tumors and inform prognosis.
Methods: An array containing 492 genes was used to generate gene expression profiles from 35 tumor samples. A hierarchical cluster algorithm was used to compare gene expression patterns among the tumor samples.