Nanosensors for cancer detection.

Cancer is a major burden in today's society and one of the leading causes of death in industrialised countries. Various avenues for the detection of cancer exist, most of which rely on standard methods, such as histology, ELISA, and PCR. Here we put the focus on nanomechanical biosensors derived from atomic force microscopy cantilevers. The versatility of this novel technology has been demonstrated in different applications and in some ways surpasses current technologies, such as microarray, quartz crystal microbalance and surface plasmon resonance. The technology enables label free biomarker detection without the necessity of target amplification in a total cellular background, such as BRAF mutation analysis in malignant melanoma. A unique application of the cantilever array format is the analysis of conformational dynamics of membrane proteins associated to surface stress changes. Another development is characterisation of exhaled breath which allows assessment of a patient's condition in a non-invasive manner.

Use of limitations of radiolabeled anti-CEA antibodies and their fragments for photoscanning detection of human colorectal carcinomas.

Fifty-three patients with histologically proven carcinoma were injected with highly purified [131I]-labeled goat antibodies or fragments of antibodies against carcinoembryonic antigen (CEA). Each patient was tested by external photoscanning 4, 24, 36 and 48 h after injection. In 22 patients (16 of 38 injected with intact antibodies, 5 of 13 with F(ab')2 fragments and 1 of 2 with Fab' fragments), an increased concentration of 131I radioactivity corresponding to the previously known tumor location was detected by photoscanning 36-48 h after injection. Blood pool and secreted radioactivity was determined in all patients by injecting 15 min before scanning, [99mTc]-labeled normal serum albumin and free 99mTc04-. The computerized subtraction of 99mTc from 131I radioactivity enhanced the definition of tumor localization in the 22 positive patients. However, in spite of the computerized subtraction, interpretation of the scans remained doubtful for 12 patients and was entirely negative for 19 additional patients. In order to provide a more objective evaluation for the specificity of the tumor localization of antibodies, 14 patients scheduled for tumor resection were injected simultaneously with [131I]-labeled antibodies or fragments and with [125I]-labeled normal goat IgG or fragments. After surgery, the radioactivity of the two isotopes present either in tumor or adjacent normal tissues was measured in a dual channel scintillation counter. The results showed that the antibodies or their fragments were 2-4 times more concentrated in the tumor than in the normal tissues. In addition, it was shown that the injected antibodies formed immune complexes with circulating CEA and that the amount of immune complexes detectable in serum was roughly proportional to the level of circulating CEA.

Sonication of removed breast implants for improved detection of subclinical infection.

BACKGROUND: Capsular fibrosis is a severe complication after breast implantation with an uncertain etiology. Microbial colonization of the prosthesis is hypothesized as a possible reason for the low-grade infection and subsequent capsular fibrosis. Current diagnostic tests consist of intraoperative swabs and tissue biopsies. Sonication of removed implants may improve the diagnosis of implant infection by detachment of biofilms from the implant surface. METHODS: Breast implants removed from patients with Baker grades 3 and 4 capsular contracture were analyzed by sonication, and the resulting sonication fluid was quantitatively cultured. RESULTS: This study investigated 22 breast implants (6 implants with Baker 3 and 16 implants with Baker 4 capsular fibrosis) from 13 patients. The mean age of the patients was 49 years (range, 31-76 years). The mean implant indwelling time was 10.4 years (range, 3 months to 30 years). Of the 22 implants, 12 were used for breast reconstruction and 10 for aesthetic procedures. The implants were located subglandularly (n = 12), submuscularly (n = 6), and subcutaneously (n = 4). Coagulase-negative staphylococci, Propionibacterium acnes, or both were detected in the sonication fluid cultures of nine implants (41%), eight of which grew significant numbers of microorganisms (>100 colonies/ml of sonication fluid). CONCLUSIONS: Sonication detected bacteria in 41% of removed breast implants. The identified bacteria belonged to normal skin flora. Further investigation is needed to determine any causal relation between biofilms and capsular fibrosis.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.