A self-mixing laser sensor design with an extended kalman filter for optimal online structure analysis and damping evaluation

We have developed a new algorithm based on the extended Kalman filter, in order to improve the resolution of an optical displacement sensor. This new non contact sensor which provides vibration measurement with a very good accuracy might be used for online quality control by measuring the damping of excited mechanical structure. This self-mixing sensor subject to weak feedback has been tested in comparison with a commercial vibrometer, to measure the frequency response function of a plate with a passive damping to be characterized, in order to show the efficiency of a damping treatment

Measuring multiple parameters in a self-mixing optical feedback system

We propose a new approach that yields the values of multiple parameters at the same time for self-mixing optical feedback interferometric systems. These parameters are the linewidth enhancement factor of Semiconductor Lasers, the optical feedback level factor as well as vibration information of a target including the frequency and the amplitude. The method is based on optical feedback interferometry. Its effectiveness has been confirmed by computer simulations and experiments

Improvement of European translational cancer research. Collaboration between comprehensive cancer centers

Even though the increasing incidence of cancer is mainly a consequence of a population with a longer life span, part of this augmentation is related to the increasing prevalence of patients living with a chronic cancer disease. To fight the problem, improved preventive strategies are mandatory in combination with an innovative health care provision that is driven by research. To overcome the weakness of translational research the OECI is proposing a practical approach as part of a strategy foreseen by the EUROCAN+PLUS feasibility study, which was launched by the EC in order to identify mechanisms for the coordination of cancer research in Europe

Whole-body bioluminescence imaging of T-cell response in PDAC models

Introduction: The location of T-cells during tumor progression and treatment provides crucial information in predicting the response in vivo. Methods: Here, we investigated, using our bioluminescent, dual color, T-cell reporter mouse, termed TbiLuc, T-cell location and function during murine PDAC tumor growth and checkpoint blockade treatment with anti-PD-1 and anti-CTLA-4. Using this model, we could visualize T-cell location and function in the tumor and the surrounding tumor microenvironment longitudinally. We used murine PDAC clones that formed in vivo tumors with either high T-cell infiltration (immunologically ‘hot’) or low T-cell infiltration (immunologically ‘cold’). Results: Differences in total T-cell bioluminescence could be seen between the ‘hot’ and ‘cold’ tumors in the TbiLuc mice. During checkpoint blockade treatment we could see in the tumor-draining lymph nodes an increase in bioluminescence on day 7 after treatment. Conclusions: In the current work, we showed that the TbiLuc mice can be used to monitor T-cell location and function during tumor growth and treatment.</p

Improved modeling of clinical data with kernel methods

Objective: Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. Methods: When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. Results: The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. Conclusion: For clinical data consisting of variables of different types, the proposed kernel function which takes into account the type and range of each variable - has shown to be a better alternative for linear and non-linear classification problems. (C) 2011 Elsevier B.V. All rights reserved

Predominance of M2 macrophages in organized thrombi in chronic thromboembolic pulmonary hypertension patients

Chronic thromboembolic pulmonary hypertension (CTEPH) is a debilitating disease characterized by thrombotic occlusion of pulmonary arteries and vasculopathy, leading to increased pulmonary vascular resistance and progressive right-sided heart failure. Thrombotic lesions in CTEPH contain CD68+ macrophages, and increasing evidence supports their role in disease pathogenesis. Macrophages are classically divided into pro-inflammatory M1 macrophages and anti-inflammatory M2 macrophages, which are involved in wound healing and tissue repair. Currently, the phenotype of macrophages and their localization within thrombotic lesions of CTEPH are largely unknown. In our study, we subclassified thrombotic lesions of CTEPH patients into developing fresh thrombi (FT) and organized thrombi (OT), based on the degree of fibrosis and remodeling. We used multiplex immunofluorescence histology to identify immune cell infiltrates in thrombotic lesions of CPTEH patients. Utilizing software-assisted cell detection and quantification, increased proportions of macrophages were observed in immune cell infiltrates of OT lesions, compared with FT. Strikingly, the proportions with a CD206+INOS− M2 phenotype were significantly higher in OT than in FT, which mainly contained unpolarized macrophages. Taken together, we observed a shift from unpolarized macrophages in FT toward an expanded population of M2 macrophages in OT, indicating a dynamic role of macrophages during CTEPH pathogenesis.</p

Multispectral imaging system based on light-emitting diodes for the detection of melanomas and basal cell carcinomas: a pilot study (Erratum)

This erratum corrects the error of an omitted author in doi: http://dx.doi.org/10.1117/1.JBO.22.6.065006This article [J. Biomed. Opt. 22(6), 065006 (2017)] was originally published online on 29 June 2017. An author was accidentally omitted from the author list. Josep Malvehy contributed to the concept and design, data collection, analysis and interpretation, and obtained funding. He has been added to the author list as shown above. This article was corrected online on 20 July 2017