BACKGROUND: It is important to know and decide when to end regimen for the quality of life of the patients. However, there is currently no clear agreement on when to terminate palliative chemotherapy. We investigated the duration between the last chemotherapy and death, and associated factors affecting patients receiving palliative care after the last chemotherapy. METHODS: We studied 242 patients who were put into palliative care ward after receiving chemotherapy and died during hospitalization from 2008 to 2009. Electronic medical records were used to gather information on demographic characteristics, types of primary cancer, and palliative chemotherapy. Then we analyzed the relationship between the clinical characteristics of patients and interval between last chemotherapy and death. RESULTS: The average survival time of patients after referral to palliative care was 17.5 days; survival time after discontinuation of chemotherapy was 103 days. Also, 104 (43.0%) patients died within 3 months and 14 (5.8%) patients died within 1 month of persistent palliative chemotherapy. Chemotherapy on patients within 3 months from their death was not associated with the social characteristics of the population. CONCLUSION: The patients who were referred to palliative care were found to have continued to receive chemotherapy within 3 months before death. However, only a small number of patients received chemotherapy within 1 month before death, which confirms that futile chemotherapy that extends to the end of life was less frequent. Doctors should be able to recognize the implications of excessive and aggressive use of chemotherapy and should actively communicate with patients about therapeutic choices.
Electronic Health Records ; Hospitalization ; Humans ; Palliative Care ; Quality of Life ; Referral and Consultation ; Sociology

PURPOSE: The exact mechanism regulating fibronectin (FN) expression in breast cancer cells has not been fully elucidated. In this study, we investigated the pharmacological mechanism of berberine (BBR) with respect to FN expression in triple-negative breast cancer (TNBC) cells. METHODS: The clinical significance of FN mRNA expression was analyzed using the Kaplan-Meier plotter database (http://kmplot.com/breast). FN mRNA and protein expression levels were analyzed by real-time polymerase chain reaction and western blotting, respectively. RESULTS: Using publicly available clinical data, we observed that high FN expression was associated with poor prognosis in patients with breast cancer. FN mRNA and protein expression was increased in TNBC cells compared with non-TNBC cells. As expected, recombinant human FN significantly induced cell spreading and adhesion in MDA-MB231 TNBC cells. We also investigated the regulatory mechanism underlying FN expression. Basal levels of FN mRNA and protein expression were downregulated by a specific activator protein-1 (AP-1) inhibitor, SR11302. Interestingly, FN expression in TNBC cells was dose-dependently decreased by BBR treatment. The level of c-Jun phosphorylation was also decreased by BBR treatment. CONCLUSION: Our findings demonstrate that FN expression is regulated via an AP-1–dependent mechanism, and that BBR suppresses FN expression in TNBC cells through inhibition of AP-1 activity.
Berberine* ; Blotting, Western ; Breast Neoplasms* ; Breast* ; Cell Adhesion ; Fibronectins* ; Humans ; Phosphorylation* ; Prognosis ; Real-Time Polymerase Chain Reaction ; RNA, Messenger ; Transcription Factor AP-1 ; Triple Negative Breast Neoplasms

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.