Model-based clustering of probability density functions

Complex data such as those where each statistical unit under study is described not by a single observation (or vector variable), but by a unit-specific sample of several or even many observations, are becoming more and more popular. Reducing these sample data by summary statistics, like the average or the median, implies that most inherent information (about variability, skewness or multi-modality) gets lost. Full information is preserved only if each unit is described by a whole distribution. This new kind of data, a.k.a. “distribution-valued data”, require the development of adequate statistical methods. This paper presents a method to group a set of probability density functions (pdfs) into homogeneous clusters, provided that the pdfs have to be estimated nonparametrically from the unit-specific data. Since elements belonging to the same cluster are naturally thought of as samples from the same probability model, the idea is to tackle the clustering problem by defining and estimating a proper mixture model on the space of pdfs. The issue of model building is challenging here because of the infinite-dimensionality and the non-Euclidean geometry of the domain space. By adopting a wavelet-based representation for the elements in the space, the task is accomplished by using mixture models for hyper-spherical data. The proposed solution is illustrated through a simulation experiment and on two real data sets.     

Analytical performance of glucometers in a tertiary care hospital

Point-of-care (POC) testing of glucose (glucometers) represents a convenient alternative to monitor glycemia since the measurement procedure is performed without delay after sampling of the capillary blood, thereby avoiding the metabolism by the blood cells of glucose present in plasma. Likely because of sample instability, there is no proficiency test provider in Brazil for this type of POC sample. In this context, this study aimed to evaluate the analytical performance of glucometers used in a tertiary care hospital. The glucometers used were the Accu-Chek Performa^® model from Roche Diagnostics, which use the principle of amperometry. The reference method was the reaction with modified hexokinase/glucose-6-phosphate in a Dimension^® device. The stability evaluation of the control samples showed that it can be performed up to 90 min after the collection of whole blood samples. In the two rounds performed, only one result of the 17 glucometers evaluated was out of the threshold of two standard deviation. Thus, this method for control of glucometers met the expectations and enabled comparing the glucometers in a hospital. Given the current quality guidelines, daily internal quality control of glucometers is recommended, besides at least two annual comparisons between the results of the glucometers and the reference method and one EQA every 3 months.     

Malva sylvestris L. extract suppresses desferrioxamine‐induced PGE2 and PGD2 release in differentiated U937 cells: the development and validation of an LC‐MS/MS method for prostaglandin quantification

Malva sylvestris is a species used worldwide as an alternative to anti‐inflammatory therapies; however, its mechanism of action remains unknown. In this paper, the anti‐inflammatory effects of M. sylvestris alcoholic extracts were evaluated by measuring the pro‐inflammatory mediators PGE₂ and PGD₂ in desferrioxamine‐stimulated phorbol 12‐myristate 13‐acetate‐differentiated U937 cells. An HPLC‐DAD fingerprint of the M. sylvestris extract was performed and caffeic acid, ferulic acid and scopoletin were identified and quantified. An HPLC‐MS/MS method was developed and validated to separate and measure the prostaglandins. The lower limits of detection (~0.5 ng/mL for PGE₂ and PGD₂) and quantification (1.0 ng/mL for PGE₂ and PGD₂) indicated that the method is highly sensitive. The calibration curves showed excellent coefficients of correlation (r > 0.99) over the range of 1.0–500.0 ng/mL, and at different levels, the accuracy ranged from 96.4 to 106.4% with an RSD < 10.0% for the precision study. This method was successfully applied using U937‐d cells. A significant dose‐dependent reduction of PGE₂ and PGD₂ levels occurred using 10 µg/mL (10.74 ± 2.86 and 9.60 ± 6.89%) and 50 µg/mL of extract (48.37 ± 3.24 and 53.06 ± 6.15%), suggesting that the anti‐inflammatory mechanisms evoked by M. sylvestris may be related to modulation of these mediators. Copyright © 2014 John Wiley & Sons, Ltd.