Efforts to standardise Ki-67 counting in breast cancer. A pilot study of the Swiss Working Group of Gyneco- and Breast Pathologists

Goals: Adjuvant chemotherapy decisions in breast cancer are increasing based on the pathologist's assessment of the proliferation fraction in the tumor. Yet, how good and how reproducible are we pathologists at providing reliable Ki-67 readings on breast carcinomas. Exactly how to count and in which areas to count within a tumor remains inadequately standardized. The Swiss Working Group of Gyneco- and Breast Pathologists has tried to appreciate this dilemma and to propose ways to obtain more reproducible results.Methods: In a first phase, 5 pathologists evaluated Ki67 counts in 10 breast cancers by exact counting (500 cells) and by eyeballing. Pathologists were free to select the region in which Ki67 was evaluated. In a second phase 16 pathologists evaluated Ki-67 counts in 3 breast cancers also by exact counting and eyeballing, but in predefined fields of interest. In both phases, Ki67 was assessed in centrally immunostained slides (ZH) and on slides immunostained in the 11 participating laboratories. In a third phase, these same 16 pathologists were once again asked to read the 3 cases from phase 2, plus three new cases, and this time exact guidelines were provided as to what exactly is considered a Ki-67 positive nucleus.Results: Discordance of Ki67 assessment was due to each of the following 4 factors: (i) pathologists' divergent definitions of what counts as a positive nucleus (ii) the mode of assessment (counting vs. eyeballing), (iii) immunostaining technique/protocol/antibody, and (iv) the selection of the area in which to count.Conclusion: Providing guidelines as to where to count (representative field in the tumor periphery and omitting hot spots) and what nuclei to count (even faintly immunostained nuclei count as positive) reduces the discordance rates of Ki67 readings between pathologists. Laboratory technique is only of minor importance (even over a large antibody dilution range), and counting nuclei does not improve accuracy, but rather aggravates deviations from the group mean values.Disclosure of Interest: None Declared

Mobile phone use and brain tumors in children and adolescents: a multicenter case-control study.

Background It has been hypothesized that children and adolescents might be more vulnerable to possible health effects from mobile phone exposure than adults. We investigated whether mobile phone use is associated with brain tumor risk among children and adolescents. Methods CEFALO is a multicenter case-control study conducted in Denmark, Sweden, Norway, and Switzerland that includes all children and adolescents aged 7-19 years who were diagnosed with a brain tumor between 2004 and 2008. We conducted interviews, in person, with 352 case patients (participation rate: 83%) and 646 control subjects (participation rate: 71%) and their parents. Control subjects were randomly selected from population registries and matched by age, sex, and geographical region. We asked about mobile phone use and included mobile phone operator records when available. Odds ratios (ORs) for brain tumor risk and 95% confidence intervals (CIs) were calculated using conditional logistic regression models. Results Regular users of mobile phones were not statistically significantly more likely to have been diagnosed with brain tumors compared with nonusers (OR = 1.36; 95% CI = 0.92 to 2.02). Children who started to use mobile phones at least 5 years ago were not at increased risk compared with those who had never regularly used mobile phones (OR = 1.26, 95% CI = 0.70 to 2.28). In a subset of study participants for whom operator recorded data were available, brain tumor risk was related to the time elapsed since the mobile phone subscription was started but not to amount of use. No increased risk of brain tumors was observed for brain areas receiving the highest amount of exposure. Conclusion The absence of an exposure-response relationship either in terms of the amount of mobile phone use or by localization of the brain tumor argues against a causal association.

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Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

Report of the Workshop on Intelligent Construction for Earthworks, April 14-16, 2008

This document summarizes the discussion and findings of a workshop on intelligent technologies for earthwork construction held in West Des Moines, Iowa, on April 14–16, 2009. This meeting follows a similar workshop conducted in 2008. The objective of the meeting was to provide a focused discussion on identifying research and implementation needs/strategies to advance intelligent compaction and automated machine guidance technologies. Technical presentations, interactive working breakout sessions, and a panel discussion comprised the workshop. About 100 attendees representing state departments of transportation, Federal Highway Administration, contractors, equipment manufacturers, and researchers participated in the workshop.

Improvement of a testing apparatus for dynamometry: procedures for penetrometry and influence of strain rate to quantify the tensile strength of soil aggregates

Soil penetration resistance (PR) and the tensile strength of aggregates (TS) are commonly used to characterize the physical and structural conditions of agricultural soils. This study aimed to assess the functionality of a dynamometry apparatus by linear speed and position control automation of its mobile base to measure PR and TS. The proposed equipment was used for PR measurement in undisturbed samples of a clayey "Nitossolo Vermelho eutroférrico" (Kandiudalfic Eutrudox) under rubber trees sampled in two positions (within and between rows). These samples were also used to measure the volumetric soil water content and bulk density, and determine the soil resistance to penetration curve (SRPC). The TS was measured in a sandy loam "Latossolo Vermelho distrófico" (LVd) - Typic Haplustox - and in a very clayey "Nitossolo Vermelho distroférrico" (NVdf) - Typic Paleudalf - under different uses: LVd under "annual crops" and "native forest", NVdf under "annual crops" and "eucalyptus plantation" (> 30 years old). To measure TS, different strain rates were applied using two dynamometry testing devices: a reference machine (0.03 mm s-1), which has been widely used in other studies, and the proposed equipment (1.55 mm s-1). The determination coefficient values of the SRPC were high (R² > 0.9), regardless of the sampling position. Mean TS values in LVd and NVdf obtained with the proposed equipment did not differ (p > 0.05) from those of the reference testing apparatus, regardless of land use and soil type. Results indicate that PR and TS can be measured faster and accurately by the proposed procedure.

Event-related potentials and changes of brain rhythm oscillations during working memory activation in patients with first-episode psychosis.

Background: Earlier contributions have documented significant changes in sensory, attention-related endogenous event-related potential (ERP) components and θ band oscillatory responses during working memory activation in patients with schizophrenia. In patients with first-episode psychosis, such studies are still scarce and mostly focused on auditory sensory processing. The present study aimed to explore whether subtle deficits of cortical activation are present in these patients before the decline of working memory performance. Methods: We assessed exogenous and endogenous ERPs and frontal θ event-related synchronization (ERS) in patients with first-episode psychosis and healthy controls who successfully performed an adapted 2-back working memory task, including 2 visual n-backworking memory tasks as well as oddball detection and passive fixation tasks. Results: We included 15 patients with first-episode psychosis and 18 controls in this study. Compared with controls, patients with first-episode psychosis displayed increased latencies of early visual ERPs and phasic θ ERS culmination peak in all conditions. However, they also showed a rapid recruitment of working memory-related neural generators, even in pure attention tasks, as indicated by the decreased N200 latency and increased amplitude of sustained θ ERS in detection compared with controls. Limitations: Owing to the limited sample size, no distinction was made between patients with first-episode psychosis with positive and negative symptoms. Although we controlled for the global load of neuroleptics, medication effect cannot be totally ruled out. Conclusion: The present findings support the concept of a blunted electroencephalographic response in patients with first-episode psychosis who recruit the maximum neural generators in simple attention conditions without being able to modulate their brain activation with increased complexity of working memory tasks.