Frequent detection of human rhinoviruses, paramyxoviruses, coronaviruses, and bocavirus during acute respiratory tract infections

Viruses are the major cause of pediatric acute respiratory tract infection (ARTI) and yet many suspected cases of infection remain uncharacterized. We employed 17 PCR assays and retrospectively screened 315 specimens selected by season from a predominantly pediatric hospital-based population. Before the Brisbane respiratory virus research study commenced, one or more predominantly viral pathogens had been detected in 15.2% (n = 48) of all specimens. The Brisbane study made an additional 206 viral detections, resulting in the identification of a microbe in 67.0% of specimens. After our study, the majority of microbes detected were RNA viruses (89.9%). Overall, human rhinoviruses (HRVs) were the most frequently identified target (n=140) followed by human adenoviruses (HAdVs; n = 25), human metapneumovirus (HMPV; n=18), human bocavirus (HBoV; n = 15), human respiratory syncytial virus (HRSV; n = 12), human coronaviruses (HCoVs; n = 11), and human herpesvirus-6 (n = 11). HRVs were the sole microbe detected in 37.8% (n = 31) of patients with suspected lower respiratory tract infection (LRTI). Genotyping of the HRV VP4/VP2 region resulted in a proposed subdivision of HRV type A into sublineages A1 and A2. Most of the genotyped HAdV strains were found to be type C. This study describes the high microbial burden imposed by HRVs, HMPV, HRSV, HCoVs, and the newly identified virus, HBoV on a predominantly paediatric hospital population with suspected acute respiratory tract infections and proposes a new formulation of viral targets for future diagnostic research studies.

Real-time PCR assays for detection of bocavirus in human specimens

The recently discovered human bocavirus (HBoV) is the first member of the family Parpoviridae, genus Bocavirus, to be potentially associated with human disease. Several studies have identified HBoV in respiratory specimens from children with acute respiratory disease, but the full spectrum of clinical disease and the epidemiology of HBoV infection remain unclear. The availability of rapid and reliable molecular diagnostics would therefore aid future studies of this novel virus. To address this, we developed two sensitive and specific real-time TaqMan PCR assays that target the HBoV NS1 and NP-1 genes. Both assays could reproducibly detect 10 copies of a recombinant DNA plasmid containing a partial region of the HBoV genome, with a dynamic range of 8 log units (10(1) to 10(8) copies). Eight blinded clinical specimen extracts positive for HBoV by an independent PCR assay were positive by both real-time assays. Among 1,178 NP swabs collected from hospitalized pneumonia patients in Sa Kaeo Province, Thailand, 53 (4.5%) were reproducibly positive for HBoV by one or both targets. Our data confirm the possible association of HBoV infection with pneumonia and demonstrate the utility of these real-time PCR assays for HBoV detection.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Detection of elevated protein modification in human cerebellum in alcoholic cerebellar degeneration

Modification of proteins by reactive ethanol metabolites has been known for some time to occur in the liver, the main site of ethanol metabolism. In more recent studies of laboratory animals, similar modifications have been detected in organs with lesser ability to metabolize ethanol, such as skeletal and cardiac muscle and brain. Such modification may alter protein function or form a neoantigen, making it a target for immune attack. We now report an analysis of protein modification derived from ethanol metabolites in human brain tissue by ELISA using adduct-specific antibodies. We obtained autopsy cerebellum samples from 10 alcoholic cerebellar degeneration cases and 10 matched controls under informed written consent from the next of kin and clearance from the UQ Human Ethics Committee. Elevated levels of protein modifications derived from acetaldehyde (unreduced-acetaldehyde and acetaldehyde-advanced glycation end-product adducts), from malondialdehyde (malondialdehyde adducts) and from combined adducts (malondialdehydeacetaldehyde (MAA) adducts) were detected in alcoholic cerebellar degeneration samples when compared to controls. Other adduct types found in liver samples, such as reduced-acetaldehyde and those derived from hydroxyethyl radicals, were not detected in brain samples. This may reflect the different routes of ethanol metabolism in the two tissues. This is the first report of elevated protein modification in alcoholic cerebellar degeneration, and suggests that such modification may play a role in the pathogenesis of brain injury. Supported by NIAAA under grant NIH AA12404 and the NHMRC (Australia) under grant #981723.

Capacity limits for the detection of changing visual features

Capacity limits in visual attention have traditionally been studied using static arrays of elements from which an observer must detect a target defined by a certain visual feature or combination of features. In the current study we use this visual search paradigm, with accuracy as the dependent variable, to examine attentional capacity limits for different visual features undergoing change over time. In Experiment 1, detectability of a single changing target was measured under conditions where the type of change (size, speed, colour), the magnitude of change, the set size and homogeneity of the unchanging distractors were all systematically varied. Psychometric function slopes were calculated for different experimental conditions and ‘change thresholds’extracted from these slopes were used in Experiment 2, in which multiple supra-threshold changes were made, simultaneously, either to a single or to two or three different stimulus elements. These experiments give an objective psychometric paradigm for measuring changes in visual features over time. Results favour object-based accounts of visual attention, and show consistent differences in the allocation of attentional capacity to different perceptual dimensions.

Detection of elevated protein modification in alcoholic cerebellar degeneration

Modification of proteins by reactive ethanol metabolites has been known, for some time, to occur in the liver, the main site of ethanol metabolism. More recently, similar modifi cation has been detected in organs with lesser ability to metabolise ethanol such as skeletal and cardiac muscle, and brain. Such modifi cation may alter protein function or form a neoantigen, making it a target for immune attack.

FDTD study of an UWB radar technique for breast tumor detection

A finite difference time domain (FDTD) method is applied to investigate capabilities of an ultra-wide band (UWB) radar system to detect a breast tumor. The first part of the investigations concerns FDTD simulations of a phantom formed by a plastic container with liquid and a small reflecting target. The second part focuses on a three-dimensional numerical breast model with a small tumor. FDTD simulations are carried out assuming a planar incident wave. Various time snap shots of the electromagnetic field are recorded to learn about the physical phenomenon of reflection and scattering in different layers of the phantom.

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Monitoring Infants By Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.

Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

Area summation in human vision at and above detection threshold

The initial image-processing stages of visual cortex are well suited to a local (patchwise) analysis of the viewed scene. But the world's structures extend over space as textures and surfaces, suggesting the need for spatial integration. Most models of contrast vision fall shy of this process because (i) the weak area summation at detection threshold is attributed to probability summation (PS) and (ii) there is little or no advantage of area well above threshold. Both of these views are challenged here. First, it is shown that results at threshold are consistent with linear summation of contrast following retinal inhomogeneity, spatial filtering, nonlinear contrast transduction and multiple sources of additive Gaussian noise. We suggest that the suprathreshold loss of the area advantage in previous studies is due to a concomitant increase in suppression from the pedestal. To overcome this confound, a novel stimulus class is designed where: (i) the observer operates on a constant retinal area, (ii) the target area is controlled within this summation field, and (iii) the pedestal is fixed in size. Using this arrangement, substantial summation is found along the entire masking function, including the region of facilitation. Our analysis shows that PS and uncertainty cannot account for the results, and that suprathreshold summation of contrast extends over at least seven target cycles of grating. © 2007 The Royal Society.

Real-time detection of DNA interactions with long-period fiber-grating-based biosensor

Using an optical biosensor based on a dual-peak long-period fiber grating, we have demonstrated the detection of interactions between biomolecules in real time. Silanization of the grating surface was successfully realized for the covalent immobilization of probe DNA, which was subsequently hybridized with the complementary target DNA sequence. It is interesting to note that the DNA biosensor was reusable after being stripped off the hybridized target DNA from the grating surface, demonstrating a function of multiple usability.

The influence of fixation points on contrast detection and discrimination of patches of grating: Masking and facilitation

The use of fixation points (FPs) in visual psychophysics is common practice, though the costs and benefits of different fixation regimens have not been compared. Here we investigate the influence of several different types of FP configurations on the contrast detection of patches of sine-wave gratings. We find that for small targets (1°), the addition of a superimposed central FP can increase thresholds by a factor of 1.3 (2.5 dB) in comparison with no FP, and a factor of 1.5 (3.6 dB) in comparison with FPs that surround the target. These results are consistent with (i) a suppressive influence on the central region of the target from a central FP, and (ii) facilitatory influences from surrounding FPs. Our analysis of the slope of the psychometric function suggests that the facilitatory influence is not due to reduction of uncertainty. Plausible candidate causes for the facilitation are: (i) sensory interactions, (ii) aids to ocular accommodation and convergence, (iii) a reduction in eye-movements and (iv) more accurate placement of the observer’s window of attention. Masking by a central FP is not found for the suprathreshold task of contrast discrimination, suggesting that the masking effects of pedestal and FP do not combine linearly. This means that estimates of the level of masking produced by a contrast pedestal can depend on the details of the fixation point.

The combination of smart hydrogels and fibre optic sensor technology for analyte detection

The subject of investigation of the present research is the use of smart hydrogels with fibre optic sensor technology. The aim was to develop a costeffective sensor platform for the detection of water in hydrocarbon media, and of dissolved inorganic analytes, namely potassium, calcium and aluminium. The fibre optic sensors in this work depend upon the use of hydrogels to either entrap chemotropic agents or to respond to external environmental changes, by changing their inherent properties, such as refractive index (RI). A review of current fibre optic technology for sensing outlined that the main principles utilised are either the measurement of signal loss or a change in wavelength of the light transmitted through the system. The signal loss principle relies on changing the conditions required for total internal reflection to occur. Hydrogels are cross-linked polymer networks that swell but do not dissolve in aqueous environments. Smart hydrogels are synthetic materials that exhibit additional properties to those inherent in their structure. In order to control the non-inherent properties, the hydrogels were fabricated with the addition of chemotropic agents. For the detection of water, hydrogels of low refractive index were synthesized using fluorinated monomers. Sulfonated monomers were used for their extreme hydrophilicity as a means of water sensing through an RI change. To enhance the sensing capability of the hydrogel, chemotropic agents, such as pH indicators and cobalt salts, were used. The system comprises of the smart hydrogel coated onto an exposed section of the fibre optic core, connected to the interrogation system measuring the difference in the signal. Information obtained was analysed using a purpose designed software. The developed sensor platform showed that an increase in the target species caused an increase in the signal lost from the sensor system, allowing for a detection of the target species. The system has potential applications in areas such as clinical point of care, water detection in fuels and the detection of dissolved ions in the water industry.