Aggregation invariance in general clustering approaches

General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.

The protective role of transferrin in Müller glial cells after iron-induced toxicity.

PURPOSE: Transferrin (Tf) expression is enhanced by aging and inflammation in humans. We investigated the role of transferrin in glial protection. METHODS: We generated transgenic mice (Tg) carrying the complete human transferrin gene on a C57Bl/6J genetic background. We studied human (hTf) and mouse (mTf) transferrin localization in Tg and wild-type (WT) C57Bl/6J mice using immunochemistry with specific antibodies. Müller glial (MG) cells were cultured from explants and characterized using cellular retinaldehyde binding protein (CRALBP) and vimentin antibodies. They were further subcultured for study. We incubated cells with FeCl(3)-nitrilotriacetate to test for the iron-induced stress response; viability was determined by direct counting and measurement of lactate dehydrogenase (LDH) activity. Tf expression was determined by reverse transcriptase-quantitative PCR with human- or mouse-specific probes. hTf and mTf in the medium were assayed by ELISA or radioimmunoassay (RIA), respectively. RESULTS: mTf was mainly localized in retinal pigment epithelium and ganglion cell layers in retina sections of both mouse lines. hTf was abundant in MG cells. The distribution of mTf and hTf mRNA was consistent with these findings. mTf and hTf were secreted into the medium of MG cell primary cultures. Cells from Tg mice secreted hTf at a particularly high level. However, both WT and Tg cell cultures lose their ability to secrete Tf after a few passages. Tg MG cells secreting hTf were more resistant to iron-induced stress toxicity than those no longer secreted hTf. Similarly, exogenous human apo-Tf, but not human holo-Tf, conferred resistance to iron-induced stress on MG cells from WT mice. CONCLUSIONS: hTf localization in MG cells from Tg mice was reminiscent of that reported for aged human retina and age-related macular degeneration, both conditions associated with iron deposition. The role of hTf in protection against toxicity in Tg MG cells probably involves an adaptive mechanism developed in neural retina to control iron-induced stress.

Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study.

BACKGROUND: Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance. METHODS: We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis. RESULTS: Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5-98.8), 80.8% specificity (72.6-87.1), positive likelihood ratio 4.9 (3.4-7.1), negative likelihood ratio 0.083 (0.022-0.32), and misclassification rate 0.20 (standard error 0.038). CONCLUSIONS: In Tanzanian children with WHO-defined clinical pneumonia, combinations of host biomarkers distinguished between end-point pneumonia, other infiltrates, and normal chest x-ray, whereas clinical variables did not. These findings generate pathophysiological hypotheses and may have potential research and clinical utility.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Treatment of Prosthetic Joint Infections

Prosthetic joint replacement is one of the most successful surgical procedures of the last century and the number of implanted artificial joints is rapidly growing. While the result of the procedure is generally positive, infections may occur leading to patient suffering, surgeon's frustration and important costs to the health system. Infection after prosthetic joint replacement is thus a feared complication as healing rates can be low, functional result poor and satisfaction of the patient abysmal. However, if a patient-adapted treatment of infected total joints is used, an overall success rate of above 90 % can be obtained. The patient-adapted treatment concept is based on five strong pillars: teamwork, understanding biofilm, proper diagnostics, proper definition and classification and patient-tailored treatment.

Example of Monte Carlo uncertainty assessment in the field of radionuclide metrology

This chapter presents possible uses and examples of Monte Carlo methods for the evaluation of uncertainties in the field of radionuclide metrology. The method is already well documented in GUM supplement 1, but here we present a more restrictive approach, where the quantities of interest calculated by the Monte Carlo method are estimators of the expectation and standard deviation of the measurand, and the Monte Carlo method is used to propagate the uncertainties of the input parameters through the measurement model. This approach is illustrated by an example of the activity calibration of a 103Pd source by liquid scintillation counting and the calculation of a linear regression on experimental data points. An electronic supplement presents some algorithms which may be used to generate random numbers with various statistical distributions, for the implementation of this Monte Carlo calculation method.

Patient-adapted treatment for prosthetic hip joint infection.

Hip joint replacement is 1 of the most successful surgical procedures of the last century and the number of replacements implanted is steadily growing. An infected hip arthroplasty is a disaster, it leads to patient suffering, surgeon's frustration and significant costs to the health system. The treatment of an infected hip replacement is challenging, healing rates can be low, functional results poor with decreased patient satisfaction. However, if a patient-adapted treatment of infected hip joints is used a success rate of above 90% can be obtained.Patient-adapted treatment is based on 5 important concepts: teamwork; understanding the biofilm; diagnostic accuracy; correct definition and classification of PJI; and patient-tailored treatment.This review presents a patient-adapted treatment strategy to prosthetic hip infection. It incorporates the best aspects of the single and staged surgical strategies and promotes the short interval philosophy for the 2-stage approach.