High natural killer cell number might identify stroke patients at risk of developing infections

Objective: To investigate early changes in leukocyte subsets and autonomic function as predictors of the development of poststroke infections. Methods: We assessed the time course of leukocyte subsets in the blood of 59 patients with acute ischemic stroke. We divided the patients into 2 groups: those who developed infections during the first 7 days after stroke onset and those who did not. We measured urinary norepinephrine and epinephrine concentrations and pulse rate variability indices within 24 hours of admission. Results: We found that the number of circulating natural killer (NK) cells within the first hours after stroke was higher in stroke patients who developed infections (mean 435 cells/mL; 95% confidence interval [CI] 321-588) than in stroke patients who did not develop infections (mean 236 cells/mL; 95% CI 186-300; p = 0.001). This was followed by a decrease in all lymphocyte subsets from admission to day 1, varying between 22% and 40%, which was not seen in patients without poststroke infection (mean increase varied between 2% and 23%; all p <0.005). In the group that developed infections, pulse rate variability revealed a decreased high frequency component. These findings all remained significant after adjustment for age and stroke volume. Conclusions: High circulating NK cell count within the first hours after ischemic stroke onset followed by a drop in all lymphocyte subsets identified patients who developed infections and may be caused by a sympathovagal imbalance with sympathetic overweight. These findings need to be validated in larger studies

Comparison of the haemostatic properties of conventional monopolar and bipolar transurethral resection of the prostate in patients on oral anticoagulants

A b s t r a c t I In nt tr ro od du uc ct ti io on n: : The aim of study is comparing the haemostatic properties of conventional monopolar resection (TURP) and bipolar transurethral resection in saline (TURIS) of the prostate in patients under chronic oral anticoagulants. M Ma at te er ri ia al l a an nd d m me et th ho od ds s: : Out of a cohort group of 550 endoscopic resections for bladder outlet obstruction, 176 patients on chronic oral anticoagulant therapy required endoscopic resection either by monopolar TURP or bipolar TURIS technology. Changes in haemoglobin, blood transfusion, and clot retention were compared between both groups. R Re es su ul lt ts s: : Mean postoperative change in haemoglobin level was -1.21 ±0.92 mg/dl in the TURP group compared to -1.29 ±0.99 mg/dl in the TURIS group (p = 0.603). The need for blood transfusions and the mean numbers of units transfused did not significantly differ between the 2 groups. Clot retention appeared in 12 patients (15%) in the TURP group compared to 13 patients (13%) in the TURIS group (p = 0.828). C Co on nc cl lu us si io on ns s: : Despite promising experimental results of better haemostasis and deeper coagulation depth, bipolar technology does not permit one to reduce the amount of blood loss when compared to patients treated by conventional monopolar technology in this study group of patients on oral anticoagulation therapy. Patients on oral anticoagulants suffer more incidents of clot retention, which sometimes results in re-hospitalisation. K Ke ey y w wo or rd ds s: : prostate, bipolar, transurethral resection of prostate

Design and optimization aids for composite control charts

A free beta computer program is demonstrated for simulation and design of composite control charts that have overall performance specifications. Composite control charts that can be designed by the software include those based on moving average, exponentially weighted moving average, and cumulative sum control charts. the software package, algorithms contained within the software, and an example of using the software to design a four-component composite cumulative sum control chart are described

Clustering noisy data in a reduced dimension space via multivariate regression trees

Cluster analysis is sensitive to noise variables intrinsically contained within high dimensional data sets. As the size of data sets increases, clustering techniques robust to noise variables must be identified. This investigation gauges the capabilities of recent clustering algorithms applied to two real data sets increasingly perturbed by superfluous noise variables. The recent techniques include mixture models of factor analysers and auto-associative multivariate regression trees. Statistical techniques are integrated to create two approaches useful for clustering noisy data: multivariate regression trees with principal component scores and multivariate regression trees with factor scores. The tree techniques generate the superior clustering results

Integrated wavelet principal component mapping for unsupervised clustering on near infra-red spectra

We introduce a new method of unsupervised cluster exploration and visualization for spectral datasets by integrating the wavelet transform, principal components and Gaussian mixture models. The Bayesian Information Criterion (BIC) and classification uncertainty performance criteria are used to guide an automated search of commonly available wavelets and adaptive wavelets. We demonstrate the effectiveness of the proposed method in elucidating and visualizing unsupervised clusters from near infrared (NIR) spectral datasets. The results show that informative feature extraction can be achieved through both commonly available wavelet bases and adaptive wavelets. However, the features from the adaptive wavelets are more favorable in conjunction with unsupervised Gaussian mixture models through a user specified internal linkage function

Joint multiple adaptive wavelet regression ensembles

Multiple adaptive discrete wavelet transforms were applied during a multiple regression of spectroscopic data for the purpose of investigating the hypothesis — does the use of different wavelets, at different points, within a spectrum, elucidate predictive capability. The model investigated was a constrained stacking regression ensemble with individual regression models chosen initially by a Bayes Metropolis search. The ensemble approach provided the ability to combine different regression models that used different types of wavelets. Models were applied to a publically available dataset, pertaining to biscuit dough, of near infrared spectra, that were measured by a FOSS 5000, and laboratory measurements of the fat, flour, sugar and moisture content.\ud \ud The resultant model, which is referred to as a joint multiple adaptive wavelet regression ensemble (JMAWRE), was found to be the superior predictive model when compared to models that used standard wavelets as part of the regression ensembles. The JMAWRE was also superior when compared to other models from literature that used the same publicly available NIR dataset

Penetration of Fluoride-Containing Self-Gelling Liquids into Human Molar Occlusal Fissures in vitro

AbstractThe bioadhesive characteristics of tablets for oral use made from modified starch, polyacrylic acid (PAA), polyethylene glycol (PEG) and sodium carboxymethylcellulose (CMC) were investigated. Adhesion force and energy were determined in-vitro and maximal adhesion time was evaluated in-vivo in human subjects. In-vitro, PAA showed the best bioadhesive properties, followed by modified maize starch and PEG with a mol. wt of 300,000-400,000 daltons. The presence of 0.1 mg of fluoride as NaF did not lead to significant differences in adhesion force and energy for the same formulation. The in-vivo bioadhesion was not strongly correlated to the in-vitro data. PAA, despite its excellent adhesion, proved to be irritating to the mucosa. PEG with a mol, wt of 200,000 daltons was subject to erosion. CMC showed good bioadhesive properties but the mechanical strength of the tablets was low. Modified maize starch tablets containing 5% (w/w) PAA and PEG with a mol. wt of 300,000 daltons proved to be the most suitable formulations for a fluoride-slow-release tablet with bioadhesive properties. In-vitro, the tablets released all of the fluoride within the 8 h period, with a high initial release. The release rate was related to the water absorption rate of the tablets. The PAA-containing formulations and the CMC formulations had the fastest release. In-vivo, fluoride levels with a minimum of 150 and a maximum of 1000 micrograms mL-1 were maintained for 8 h in the oral cavity. These fluoride levels were sustained significantly longer than those obtained with the administration of fourfold the amount of fluoride in the form of a fluoride-containing toothpaste. The release characteristics in-vivo exhibited a high variation. The use of bioadhesive polymers in oral pharmacotherapy seems promising.info:eu-repo/semantics/publishe

Integrated feature extraction using adaptive wavelets

On-line quality control in the manufacturing and processing industry is increasingly being undertaken by analyzing collinear data such as spectra sampled by a spectrometer. Spectral data are very highly dimensional and are characterized by having highly correlated, localized structures. Wavelets are therefore most effective in extracting the important local features in spectra by reducing the number of variables whilst, at the same time, retaining as much information as possible and facilitating the automated analysis and interpretation of spectra. There are many kinds of wavelets which exist in the literature, but the fundamental problem to overcome is deciding which wavelet will produce the best results for a particular application. Rather than using an 'off-the-shelf' wavelet, an automated search is performed for the wavelet which optimizes specified multivariate modeling criteria. The spectral data analyzed in this chapter are of importance to the agricultural, pharmaceutical and mining industries as well as the environmental sciences