Serum proteomic abnormality predating screen detection of ovarian cancer

Ovarian cancer is characterized by vague, non-specific symptoms, advanced stage at diagnosis and poor overall survival. A nested case control study was undertaken on stored serial serum samples from women who developed ovarian cancer and healthy controls (matched for serum processing and storage conditions as well as attributes such as age) in a pilot randomized controlled trial of ovarian cancer screening. The unique feature of this study is that the women were screened for up to 7 years. The serum samples underwent prefractionation using a reversed-phase batch extraction protocol prior to MALDI-TOF MS data acquisition. Our exploratory analysis shows that combining a single MS peak with CA125 allows statistically significant discrimination at the 5% level between cases and controls up to 12 months in advance of the original diagnosis of ovarian cancer. Such combinations work much better than a single peak or CA125 alone. This paper demonstrates that mass spectra from the low molecular weight serum proteome carry information useful for early detection of ovarian cancer. The next step is to identify the specific biomarkers that make early detection possible.

Lag-time effects on a naturally ventilated large thermometer screen

Systematic natural ventilation effects on measured temperatures within a standard large wooden thermometer screen are investigated under summer conditions, using well-calibrated platinum resistance thermometers. Under low ventilation (2mwind speed u2 < 1.1 m s−1), the screen slightly underestimates daytime air temperature but overestimates air temperature nocturnally by 0.2◦C. The screen’s lag time L lengthens with decreasing wind speed, following an inverse power law relationship between L and u2. For u2 > 2 m s−1, L ∼ 2.5 min, increasing, when calm, to at least 15 min. Spectral response properties of the screen to air temperature fluctuations vary with wind speed because of the lag changes. Ventilation effects are particularly apparent at the higher (>25◦C) temperatures, both through the lag effect and from solar heating. For sites where wind speed decreases with increasing daytime temperature, thermometer screen temperatures may consequently show larger uncertainties at the higher temperatures. Under strong direct beam solar radiation (>850W m−2) the radiation effect is likely to be <0.4◦C. Copyright c 2011 RoyalMeteorological Society

Application of logistic regression for fault analysis in an industrial printing process

A statistical technique for fault analysis in industrial printing is reported. The method specifically deals with binary data, for which the results of the production process fall into two categories, rejected or accepted. The method is referred to as logistic regression, and is capable of predicting future fault occurrences by the analysis of current measurements from machine parts sensors. Individual analysis of each type of fault can determine which parts of the plant have a significant influence on the occurrence of such faults; it is also possible to infer which measurable process parameters have no significant influence on the generation of these faults. Information derived from the analysis can be helpful in the operator's interpretation of the current state of the plant. Appropriate actions may then be taken to prevent potential faults from occurring. The algorithm is being implemented as part of an applied self-learning expert system.