On the variation with flux and frequency of the core loss coefficients in electrical machines

A model of core losses, in which the hysteresis coefficients are variable with the frequency and induction (flux density) and the eddy-current and excess loss coefficients are variable only with the induction, is proposed. A procedure for identifying the model coefficients from multifrequency Epstein tests is described, and examples are provided for three typical grades of non-grain-oriented laminated steel suitable for electric motor manufacturing. Over a wide range of frequencies between 20-400 Hz and inductions from 0.05 to 2 T, the new model yielded much lower errors for the specific core losses than conventional models. The applicability of the model for electric machine analysis is also discussed, and examples from an interior permanent-magnet and an induction motor are included

Computation of core losses in electrical machines using improved models for laminated steel

Two new models for specific power losses in cold-rolled motor lamination steel are described together with procedures for coefficient identification from standard multifrequency Epstein or single sheet tests. The eddy-current and hysteresis loss coefficients of the improved models are dependent on induction (flux density) and/or frequency, and the errors are substantially lower than those of conventional models over a very wide range of sinusoidal excitation, from 20 Hz to 2 kHz and from 0.05 up to 2 T. The model that considers the coefficients to be variable, with the exception of the hysteresis loss power coefficient that has a constant value of 2, is superior in terms of applicability and phenomenological support. Also included are a comparative study of the material models on three samples of typical steel, mathematical formulations for the extension from the frequency to the time domain, and examples of validation from electrical machine studies

Human papillomavirus detection and comorbidity: critical issues in selection of patients with oropharyngeal cancer for treatment De-escalation trials

The presence of human papillomavirus (HPV)-infection in oropharyngeal squamous cell carcinoma (OPSCC) is a major determinant in prognostic risk modeling. However, most risk models are based on clinical trials which only include a selected patient population. The clinical significance of HPV and other prognostic factors in patients with OPSCC remains to be evaluated in a large, unselected cohort, which also includes patients with stage I/II disease and patients with severe comorbidity. All patients diagnosed with OPSCC in 2000-2006 in two Dutch university hospitals were included. The presence of an oncogenic HPV infection was determined by p16-immunostaining, followed by a high-risk HPV general primer 5+/6+ DNA PCR on the p16-positive cases. Cox regression analysis was carried out to compare survival rates between HPV-positive and HPV-negative patients and a prognostic model was generated by recursive partitioning. In total, 163 of 841 (19.4%) tumors were HPV-positive. Patients with HPV-positive OPSCC had a more favorable overall survival [73.5% versus 40.9% after 5 years; P < 0.001; hazard ratio = 0.34, 95% confidence interval (CI) 0.25-0.48] compared with patients with HPV-negative OPSCC. Patients with p16-positive but HPV DNA-negative tumors showed a significantly less favorable survival than patients with p16-positive and HPV DNA-positive tumors (P < 0.001). A prognostic model was developed in which pa Tumor HPV status is a strong and independent prognostic factor for survival among patients with OPSCC. A prognostic risk model was proposed, based on our large, unselected cohort of patients with HPV status, comorbidity and nodal stage being the important prognostic factors. In addition, this study emphasizes the importance of performing an HPV DNA-specific test besides p16-immunostaining

Increasing prevalence rates of HPV attributable oropharyngeal squamous cell carcinomas in the Netherlands as assessed by a validated test algorithm

Human papillomavirus (HPV) infection has been etiologically linked to oropharyngeal squamous cell carcinoma (OPSCC). The prevalence of HPV-positive OPSCC varies between studies, ranging from 20 to 90%. This may be related to the lack of a standardized HPV detection assay as well as to the time period in which HPV prevalence is investigated, as rising incidence rates are reported over the last decades. Here, we validated our previously defined test algorithm for HPV detection in formalin-fixed paraffin-embedded (FFPE) tumor specimen consisting of p16INK4A immunostaining followed by high-risk HPV DNA detection by GP5+/6+ PCR on the positive cases (Smeets et al., Int J Cancer 2007;121:2465-72). In addition, we analyzed HPV prevalence rates in OPSCCs in the years 1990-2010. The test algorithm was validated on a consecutive series of 86 OPSCCs collected during 2008-2011, of which both fresh frozen and FFPE samples were available. We performed HPV-E6 RT-PCR on the frozen samples as gold standard and applied the algorithm to the corresponding FFPE samples. The test algorithm showed an accuracy of 98%. Using the validated algorithm, we determined the presence of an oncogenic HPV infection in 240 OPSCCs of patients diagnosed in the years 1990-2010 at our center. A significant increase in the proportion of HPV-positive samples was observed, from 5.1% in 1990 to 29.0% in 2010 (p = 0.001). In conclusion, we confirmed the accuracy of the test algorithm for HPV detection in FFPE tumor specimen and we found a significant increase in the prevalence of HPV in OPSCC over the last two decades at our center

Molecular characterization of p16-immunopositive but HPV DNA-negative oropharyngeal carcinomas

Recent studies have reported that p16 protein overexpression qualifies as a surrogate marker identifying an oncogenic human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma (OPSCC). However, there is still a percentage of OPSCCs that are positive for p16 immunohistochemistry (p16 IHC) but lack HPV DNA. The objective of this study was to characterize this group at the molecular level by performing sensitive HPV DNA- and RNA-based PCR methods and genetic profiling. All patients diagnosed with an OPSCC in the period 2000-2006 in two Dutch university medical centers were included (n = 841). The presence of HPV in a tumor sample was tested by p16 IHC followed by an HPV DNA GP5+/6+ PCR. p16 IHC scored positive in 195 samples, of which 161 were HPV DNA-positive and 34 (17%) HPV DNA-negative. In the latter group, a SPF10-LiPA25 assay, an HPV16 type-specific E7 PCR and an E6 mRNA RT-PCR were performed. Next, ten of these cases were further analyzed for loss of heterozygosity (LOH) of 15 microsatellite markers at chromosome arms 3p, 9p and 17p. Of the 34 p16-positive but PCR-negative OPSCCs, two samples tested positive by SPF10 assay, HPV16 E7 PCR and HPV16 E6 mRNA RT-PCR. Three samples tested positive by SPF10 assay but negative by the HPV16-specific assays. Nine of ten cases that were tested for LOH showed a genetic pattern comparable to that of HPV-negative tumors. This study categorizes p16-positive but HPV DNA-negative OPSCCs as HPV-negative tumors based on genetic profiling. This study highlights the importance of performing HPV testing in addition to p16 IHC for proper identification of HPV-associated OPSCCs

DNA hypermethylation analysis in sputum for the diagnosis of lung cancer: training validation set approach

Lung cancer has the highest mortality of all cancers. The aim of this study was to examine DNA hypermethylation in sputum and validate its diagnostic accuracy for lung cancer. DNA hypermethylation of RASSF1A, APC, cytoglobin, 3OST2, PRDM14, FAM19A4 and PHACTR3 was analysed in sputum samples from symptomatic lung cancer patients and controls (learning set: 73 cases, 86 controls; validation set: 159 cases, 154 controls) by quantitative methylation-specific PCR. Three statistical models were used: (i) cutoff based on Youden's J index, (ii) cutoff based on fixed specificity per marker of 96% and (iii) risk classification of post-test probabilities. In the learning set, approach (i) showed that RASSF1A was best able to distinguish cases from controls (sensitivity 42.5%, specificity 96.5%). RASSF1A, 3OST2 and PRDM14 combined demonstrated a sensitivity of 82.2% with a specificity of 66.3%. Approach (ii) yielded a combination rule of RASSF1A, 3OST2 and PHACTR3 (sensitivity 67.1%, specificity 89.5%). The risk model (approach iii) distributed the cases over all risk categories. All methods displayed similar and consistent results in the validation set. Our findings underscore the impact of DNA methylation markers in symptomatic lung cancer diagnosis. RASSF1A is validated as diagnostic marker in lung cance