Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Immediate restoration of nonsubmerged titanium implants with a sandblasted and acid-etched surface: five-year results of a prospective case series study using clinical and radiographic data

The aim of this study was to evaluate the survival and success rates of immediately restored implants with sandblasted, large-grit, acid-etched (SLA) surfaces over a period of 5 years. Twenty patients (mean age, 47.3 years) received a total of 21 SLA wide-neck implants in healed mandibular first molar sites after initial periodontal treatment. To be included in the study, the implants had to demonstrate primary stability with an insertion torque value of 35 Ncm. A provisional restoration was fabricated chairside and placed on the day of surgery. Definitive cemented restorations were inserted 8 weeks after surgery. Community Periodontal Index of Treatment Needs (CPITN) indices and the radiographic distance between the implant shoulder and the first visible bone-implant contact (DIB) were measured and compared over the study period. The initial mean CPITN was 3.24, and decreased over the study period to 1.43. At the postoperative radiographic examination, the mean DIB was 1.41 mm for the 21 implants, indicating that part of the machined neck of the implants was placed slightly below the osseous crest. The mean DIB value increased to 1.99 mm at the 5-year examination. This increase proved to be statistically significant (P < .0001). Between the baseline and 5-year examinations, the mean bone crest level loss was 0.58 mm. Success and survival rates of the 21 implants after 5 years of function were 100%. This 5-year study confirms that immediate restoration of mandibular molar wide-neck implants with good primary stability, as noted by insertion torque values of at least 35 Ncm, is a safe and predictable procedure.

Uranium mining industry views on ICRP statement on radon

In 2009, the International Commission on Radiological Protection issued a statement on radon which stated that the dose conversion factor for radon progeny would likely double, and the calculation of risk from radon should move to a dosimetric approach, rather than the longstanding epidemiological approach. Through the World Nuclear Association, whose members represent over 90% of the world's uranium production, industry has been examining this issue with a goal of offering expertise and knowledge to assist with the practical implementation of these evolutionary changes to evaluating the risk from radon progeny. Industry supports the continuing use of the most current epidemiological data as a basis for risk calculation, but believes that further examination of these results is needed to better understand the level of conservatism in the potential epidemiological-based risk models. With regard to adoption of the dosimetric approach, industry believes that further work is needed before this is a practical option. In particular, this work should include a clear demonstration of the validation of the dosimetric model which includes how smoking is handled, the establishment of a practical measurement protocol, and the collection of relevant data for modern workplaces. Industry is actively working to address the latter two items.

TA-RE: An Exchange Language for Mining Software Repositories

Software repositories have been getting a lot of attention from researchers in recent years. In order to analyze software repositories, it is necessary to first extract raw data from the version control and problem tracking systems. This poses two challenges: (1) extraction requires a non-trivial effort, and (2) the results depend on the heuristics used during extraction. These challenges burden researchers that are new to the community and make it difficult to benchmark software repository mining since it is almost impossible to reproduce experiments done by another team. In this paper we present the TA-RE corpus. TA-RE collects extracted data from software repositories in order to build a collection of projects that will simplify extraction process. Additionally the collection can be used for benchmarking. As the first step we propose an exchange language capable of making sharing and reusing data as simple as possible.