Utility of scintigraphic methods in patients with fever of unknown origin

BACKGROUND: We assessed the utility of scintigraphy with indium 111-labeled polyclonal human IgG scintigraphy in patients with fever of unknown origin that fulfilled the criteria of temperature of 38.3 degrees C or more for at least 3 weeks and no diagnosis during 1 week of hospital admission. We compared the utility of this technique with results of scintigraphic techniques reported in the literature. METHODS: Data for all patients seen at our university hospital in whom 111In-IgG scanning was performed were analyzed and checked for the criteria for fever of unknown origin. The literature on the utility of scintigraphic techniques in patients with fever of unknown origin was reviewed. RESULTS: We studied 24 patients with fever of unknown origin. In 13 patients, focal 111In-IgG accumulation was observed. In nine (38%) of those, the positive 111In-IgG scintigram led to the final diagnosis; in the other four patients (17%), the scintigraphic findings were not helpful. In the 11 patients with negative 111In-IgG scans, extensive diagnostic workup produced no infection as the final diagnosis in nine patients (38%), one had an abscess in a renal cyst that was detected several months later, and in the other the cause of fever was an infected intravenous line. The overall sensitivity and specificity of 111In-IgG scintigraphy were 81% and 69%, respectively. The positive predictive value was 69% and the negative predictive value was 82%. CONCLUSIONS: Our results show that 111In-IgG scintigraphy significantly contributed to the diagnostic process in patients with fever of unknown origin. A positive scan increased the likelihood of finding the cause of the fever, and a negative scan ruled out an inflammatory component with a high degree of certainty. These data compare favorably with data in the literature concerning other radiopharmaceuticals; a larger prospective evaluation of this technique is indicated.     

Proteomics of plaques and novel sources of potential biomarkers for atherosclerosis

Cardiovascular disease (CVD) is the leading cause of death and loss of productive life years in the world. The underlying syndrome of CVD, atherosclerosis, is a complex disease process, which involves lipid metabolism, inflammation, innate and adaptive immunity, and many other pathophysiological aspects. Furthermore, CVD is influenced by genetic as well as environmental factors. Early detection of CVD and identification of patients at risk are crucial to reduce the burden of disease and to allow personalized treatment. As established risk factors fail to accurately predict which part of the population is likely to suffer from the disease, novel biomarkers are urgently needed. Proteomics can play a significant role in identifying these biomarkers. In this review, we describe the progress made in proteome profiling of the atherosclerotic plaque and several novel sources of potential biomarkers, including circulating cells and plasma extracellular vesicles. The importance of longitudinal biobanking in biomarker discovery is highlighted and exemplified by several plaque proteins identified in the biobank study Athero-Express. Finally, we discuss the PTMs of proteins that are involved in atherosclerosis, which may become one of the foci in the ongoing quest for biomarkers through proteomics of plaque and other matrices relevant to the progression of atherosclerosis.     

An efficient and robust method for Lagrangian magnetic particle tracking in fluid flow simulations on unstructured grids

In this paper we report on a newly developed particle tracking scheme for fluid flow simulations on 3D unstructured grids, aiming to provide detailed insights in the particle behaviour in complex geometries. A possible field of applications is the magnetic drug targeting (MDT) technique, on which this paper will be focused. MDT is a promising medical technique that uses locally applied magnetic fields to capture magnetic drug carriers at the desired locations in the human body, strongly increasing the efficiency of medical drugs. The new particle tracking scheme combines the advantages of existing methods and is easy for implementation in a generic numerical code. The scheme is tested and validated for simple MDT cases that include effects of a non-homogeneous magnetic field on deposition of magnetic particles in laminar flow. The first test case is a validation study of the magnetic particle trajectories released in a horizontal circular pipe flow with a current-carrying wire parallel to the flow, for which analytical solutions are reported in literature. The second test case involves particle capture efficiencies in a 90° bent tube for different configurations of the imposed magnetic field. This configuration corresponds more closely to the conditions inside blood vessels, because of the presence of secondary motions. These results are compared with numerical studies from literature too. The obtained results demonstrate that the developed particle tracking scheme is a very robust, efficient and accurate method, which can give detailed insights in particle behaviour in complex geometries. As such it is a good candidate for future applications and optimisations of MDT technique for loco-regional cancer treatment or treatment of cardiovascular diseases.     

Electroactive behavior assessment of poly(acrylic acid)‐graphene oxide composite hydrogel in the detection of cadmium

Super absorbent polymers of acrylic acid‐graphene oxide (PAA‐GO) were synthesized with different percentage of chemical neutralization (0, 10, and 20%) of the acrylic acid monomer before its polymerization. The influence of their swelling and adsorption/desorption capacity of cadmium ions in aqueous solutions were studied and revealed that the GO enables greater mechanical stability in the materials. The PAA hydrogels, with the same degrees of neutralization, were also prepared without GO to compare with the composites. Additionally, carbon paste electrodes (CPE) modified with the composites PAA‐GO were used to asses and compare their adsorption properties with cadmium(II). The anodic stripping voltammetry (ASV) peak, in the differential pulse voltammetry mode, for cadmium oxidation was found to be influenced by the presence of GO into the polymer, and also by their percentage of neutralization. The accumulation of cadmium(II) on the surface of the modified CPEs was performed under open‐circuit conditions taking an account the preconcentration time of the metal cation. The presence of GO enhances the electrical signal of the electrodes in short times of immersion in cadmium(II) solutions. This property contributed to get linear responses of the CPEs modified with the composites, which were influenced by their degrees of neutralization. The PAA‐GO 10N electrode with 10% of neutralization combined the influence of GO and the degree of neutralization in the same matrix, and also showed good performance in terms of its mechanical stability, it was chosen for preliminary studies on the selectivity of the electrode toward Zn(II) and Cu(II). © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40846.     

The Sensitivity Matrix: Using Advanced Auditory Models in Speech and Audio Processing

Perceptually optimal processing of speech and audio signals demands a rigorous approach using a distortion measure that resembles human perception. This requires distortion measures based on sophisticated, complex auditory models. Under the assumption of small distortions these models can be simplified by means of a sensitivity matrix. In this paper, we show the power of this approach. We present a method to derive the sensitivity matrix for distortion measures based on spectro-temporal auditory models. This method is applied to an example auditory model and the region of validity of the approximation and the application of linear algebra to analyze the characteristics of the given model are discussed. Furthermore, we show how to build a coder minimizing a sensitivity matrix distortion measure given the typically long support of a perceptual distortion measure     

On the Estimation of Differential Entropy From Data Located on Embedded Manifolds

Estimation of the differential entropy from observations of a random variable is of great importance for a wide range of signal processing applications such as source coding, pattern recognition, hypothesis testing, and blind source separation. In this paper, we present a method for estimation of the Shannon differential entropy that accounts for embedded manifolds. The method is based on high-rate quantization theory and forms an extension of the classical nearest-neighbor entropy estimator. The estimator is consistent in the mean square sense and an upper bound on the rate of convergence of the estimator is given. Because of the close connection between compression and Shannon entropy, the proposed method has an advantage over methods estimating the Renyi entropy. Through experiments on uniformly distributed data on known manifolds and real-world speech data we show the accuracy and usefulness of our proposed method.     

Estimation of the short-term predictor parameters of speech under noisy conditions

Speech coding algorithms that have been developed for clean speech are often used in a noisy environment. We describe maximum a posteriori (MAP) and minimum mean square error (MMSE) techniques to estimate the clean-speech short-term predictor (STP) parameters from noisy speech. The MAP and MMSE estimates are obtained using a likelihood function computed by means of the DFT or Kalman filtering and empirical probability distributions based on multidimensional histograms. The method is assessed in terms of the resulting root mean spectral distortion between the "clean" speech STP parameters and the STP parameters computed with the proposed method from noisy speech. The estimated parameters are also applied to obtain clean speech estimates by means of a Kalman filter. The quality of the estimated speech as compared to the "clean" speech is assessed by means of subjective tests, signal-to-noise ratio improvement, and the perceptual speech quality measurement method.     

HMM-Based Gain Modeling for Enhancement of Speech in Noise

Accurate modeling and estimation of speech and noise gains facilitate good performance of speech enhancement methods using data-driven prior models. In this paper, we propose a hidden Markov model (HMM)-based speech enhancement method using explicit gain modeling. Through the introduction of stochastic gain variables, energy variation in both speech and noise is explicitly modeled in a unified framework. The speech gain models the energy variations of the speech phones, typically due to differences in pronunciation and/or different vocalizations of individual speakers. The noise gain helps to improve the tracking of the time-varying energy of nonstationary noise. The expectation-maximization (EM) algorithm is used to perform offline estimation of the time-invariant model parameters. The time-varying model parameters are estimated online using the recursive EM algorithm. The proposed gain modeling techniques are applied to a novel Bayesian speech estimator, and the performance of the proposed enhancement method is evaluated through objective and subjective tests. The experimental results confirm the advantage of explicit gain modeling, particularly for nonstationary noise sources     

Numerical study of the Stratified smoke flow in a corridor: Full-scale calculations

The two-dimensional, steady-state, turbulent flow of hot air and smoke in a corridor with an adjacent room fire is calculated numerically. Turbulence is accounted for through the k-ε model. Buoyancy efects are included in both the vertical momentum and the turbulence equations. Convective and radiative heat losses are accounted for. The simple radiation model used assumes a well-mixed, spectrally gray and optically thick smoke layer.

A full-sized corridor of 75 m length and 2.5 m height is considered. Parameter variations include inflow temperature, radiative heat losses and net mass flow. Special attention is given to the stratification of the hot smoke layer. Strong stratification is found for all situations considered. However, the hot layer thickness increases significantly in some cases. Our calculations do not support the use of a critical overall Richardson number as a criterion for the occurrence of stratification.     

Ultrastrong Anchoring Yet Barrier‐Free Adsorption of Composite Microgels at Liquid Interfaces

Microgel particles display an interesting duality with properties attributed typically both to polymeric and colloidal systems. When adsorbed at a liquid‐liquid interface, this duality becomes particularly apparent as the various phenomena at play are governed by different aspects of these soft and responsive particles. The introduction of a solid, fluorescently labeled, polystyrene core into the microgels allows direct and accurate visualization without the necessity of potential perturbing sample preparation techniques. By combining in‐situ imaging and tensiometry, we determine that composite microgels at a wide variety of oil‐water interfaces anchor strongly, with adsorption energies of approximately 10⁶ k_BT, typical for particle adsorption, yet accumulate at the interface spontaneously without any energy barrier, which is more typical for polymers. The high adsorption energies allow the particle to spontaneously form very dense crystalline packings at the liquid interface in which the microgels are significantly compressed with respect to their swollen state in bulk solutions. Finally, we demonstrate the unique nature of these particles by producing highly stable and monodisperse microgel‐stabilized droplets using microfluidics.