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Sperm protein 17 (Sp17) is selectively overexpressed in several human malignancies including ovarian carcinoma, but is absent or expressed at low levels in most normal tissues. Previous work from our group characterized an anti-Sp17 monoclonal antibody (clone 3C12) and showed that it specifically targeted tumor cells. In this report, we investigated whether a novel immunoconjugate containing 3C12 linked to the chemotherapeutic agent doxorubicin [(DOX) Adriamycin] had antitumor activity against ovarian cancer cell lines and tumor models. DOX was conjugated to 3C12 using a linker, and the specificity of 3C12-DOX was examined in Sp17-positive SKOV3 and Sp17-negative COC2 ovarian cancer cells using cell-based ELISA and internalization assays. The cytotoxicity of 3C12-DOX was assessed with the MTT assay, and its therapeutic effectiveness was evaluated in immunodeficient mice bearing SKOV3 cells. In vitro, the 3C12-DOX immunoconjugate specifically bound to and was internalized by Sp17-positive SKOV3 cells but did not bind to Sp17-negative cells. Treatment with 3C12-DOX (0.001 to 10 μg/mL) decreased the viability of SKOV3 cells in a Sp17-specific manner. In vivo, 3C12-DOX (3 mg/kg) induced the regression of established SKOV3 xenograft tumors in BALB/c mice compared with control treatment. The antitumor effects of 3C12-DOX were significantly associated with the induction of apoptosis in tumor cells. In addition, 3C12-DOX showed no observable adverse effects or toxicity when compared with DOX alone in mice bearing ovarian tumor xenografts. Our findings suggest that 3C12-DOX may be a potential antibody-drug conjugate for clinical development.

Background Bloodstream infections due to Candida species cause significant morbidity and mortality, and the epidemiology of Candida infection is changing. Surveillance for candidemia is necessary to detect trends in species distribution and antifungal resistance. Methods The medical and electronic records of all patients who had candidemia at the authors’ hospital from 2009 to 2011 were reviewed for demographic data and clinical information, including the infecting Candida species, resistance to antifungals and survival, and the presence of risk factors associated with candidemia. Results A total of 133 distinct episodes of candidemia were identified over the study period. The annual incidence of candidemia ranged between 0.71 and 0.85 cases/1000 hospital discharges. The most frequent Candida species were C. tropicalis (28.6%), followed by C. albicans (23.3%) and C. parapsilosis (19.5%). The rates of susceptibility to antifungal agents were as followed: voriconazole (97.8%), itraconazole (69.5%), fluconazole (46.1%), ketoconazole (38.9%). Out of 131 evaluable patients, 34 (26.0%) died within 30 days from the onset of candidemia. C. tropicalis candidemia was associated with the highest mortality rate (44.7%). Regarding the crude mortality in the different units, patients in Hemato-Oncology ward had the highest mortality rate (66.7%), followed by patients in cardiovascular wards and ICU (57.1% and 25.6%, respectively). Predictors of 30-day mortality were identified by uni- and multivariate analyses. Complicated abdominal surgery, presence of central venous catheter (CVC), neutropenia, candidemia due to C. tropicalis and poor treatment with fluconazole were significantly associated with the 30-day mortality. Presence of CVC (odds ratio[OR] = 4.177; 95% confidence interval [CI] = 1.698 to 10.278; P = 0.002) was the only independent predictor for mortality in the multivariate analysis. Conclusion This report provides baseline data for future epidemiological and susceptibility studies and for the mortality rates associated with candidemia in our hospital. The knowledge of the local epidemiological trends in Candida species isolated in blood cultures is important to guide therapeutic choices.

Various fault types and difficult diagnosis restricted the improvement of economic benefit and system efficiency of electrical submersible progressing cavity pump (ESPCP) production system. A novel method for status recognition of electrical parameters in fault diagnosis of ESPCP based on biomimetic pattern recognition (BPR) is presented. Application results show the proposed BPR classifier produces significant accuracy for classification of ESPCP electrical parameters. Compared with the results based on support vector machine (SVM), the proposed method is more efficiency.