Determination of diphenhydramine by capillary electrophoresis with tris(2,2 '-bipyridyl)ruthenium(II) electrochemiluminescence detection

Tris(2,2'-bipyridyl)ruthenium(II) electrochemiluminescence detection in a capillary electrophoresis separation system was used for the determination of diphenhydramine. In this study, platinum disk electrode (300 mum in diameter) was used as a working electrode and the influence of applied potential and buffer conditions were investigated. Under optimal conditions: 1.2 V applied potential, pH 8.50, 15 kV separation voltage and 10 mmol l(-1) running buffer, the calibration curve of diphenhydramine was linear over the range of 4 x 10(-8) to 1 x 10(-5) Mol l(-1). This technique gave satisfactory precision, and relative standard deviations of migration times and chemiluminescence peak intensities were less than 1 and 6%, respectively. The technique was applied to animal studies for determination of diphenhydramine extracted from rabbit plasma and urine samples, and the extraction efficiency were between 92 and 98.5%.

Capillary electrophoresis with amperometric detection of curcumin in Chinese herbal medicine pretreated by solid-phase extraction

In the present study, curcumin from Chinese herbal medicine turmeric was determined by capillary electrophoresis with amperometric detection (CE-AD) pretreated by a self-designed, simple, inexpensive solid-phase extraction (SPE) cartridge based on the material of tributyl phosphate resin. An average concentration factor of 9 with the recovery of >80% was achieved when applied to the analysis of curcumin in extracts of turmeric. Under the optimized CE-AD conditions: a running buffer composed of 15 mM phosphate buffer at a pH 9.7, separation voltage at 16 W, injection for 6 s at 9 W and detection at 1.20 V, CE-AD with SPE exhibited low detection limit as 3 - 10(-8) mol/l (SIN = 3), high efficiency of 1.0(.)10(5) N, linear range of 7(.)10(-4) -3(.)10(-6) mol/l (r = 0.9986) for curcumin extracted from light petroleum. The method developed resulted in enhancement of the detection sensitivity and reduction of interference from sample matrix in complicated samples and exhibited the potential application for routine analysis, especially in food, because a relatively complete process of sample treatment and analysis was described.

Progress in amperometric detection for capillary electrophoresis

As a high efficiency separation technique, capillary electrophoresis(CE) has been widely used in various fields of analytical science. Amperometry is one of the most sensitive electrochemical detection methods in CE. The capillary/electrode decoupling mechanism, applications,of new electrode systems in CE, detection cell technique are discussed in detail. Amperometric detection is compatible with microfabricated CE chips and will make the concept of lab-on-a-chip become a reality. Because of these progresses, amperometry is becoming a widely acceptable detection method,for more chemical and biological analytes.

Determination of allopurinol and its active metabolite oxypurinol by capillary electrophoresis with end-column amperometric detection

A simple method was proposed for the separation of allopurinol (AP) and its active metabolite oxypurinol (OP) by capillary electrophoresis with end-column amperometric detection. A running buffer composed of 15 rum Na2HPO4/NaH2PO4 at a pH 9.55, electrokinetic injection 7 s at 5 kV, separation voltage at 15 kV and detection potential at 1.20 V were investigated to be the optimal condition for the separation. The method exhibited low detection Emit (S/N = 3) as 1 x 10(-8) mol/l for AP and OP, wide linearity range of 2 x 10(-7) to 1 x 10(-4) mol/l, 1 x 10(-7) to 1 x 10(-4) and high efficiency of 1.2 x 10(5) and 1.8 x 10(5) N/m for AP and OP, respectively. The potential application examined for the method was the determination of the spiked urine sample, which was proved to be sensitive and efficient. (C) 2001 Elsevier Science B.V. All rights reserved.

The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.

Proposed wavelet-neurofuzzy combined system for power qualityviolations detection and diagnosis

A system for the identification of power quality violations is proposed. It is a two-stage system that employs the potentials of the wavelet transform and the adaptive neurofuzzy networks. For the first stage, the wavelet multiresolution signal analysis is exploited to denoise and then decompose the monitored signals of the power quality events to extract its detailed information. A new optimal feature-vector is suggested and adopted in learning the neurofuzzy classifier. Thus, the amount of needed training data is extensively reduced. A modified organisation map of the neurofuzzy classifier has significantly improved the diagnosis efficiency. Simulation results confirm the aptness and the capability of the proposed system in power quality violations detection and automatic diagnosis

Maximising capture efficiency and specificity of magnetic separation for Mycobacterium avium subsp. paratuberculosis cells

In order to introduce specificity for Mycobacterium avium subsp. paratuberculosis prior to a phage amplification assay, various magnetic-separation approaches, involving either antibodies or peptides, were evaluated in terms of the efficiency of capture (expressed as a percentage) of M. avium subsp. paratuberculosis cells and the percentage of nonspecific binding by other Mycobacterium spp. A 50:50 mixture of MyOne Tosylactivated Dynabeads coated with the chemically synthesized M. avium subsp. paratuberculosis-specific peptides biotinylated aMp3 and biotinylated aMptD (i.e., peptide-mediated magnetic separation [PMS]) proved to be the best magnetic-separation approach for achieving 85 to 100% capture of M. avium subsp. paratuberculosis and minimal (<1%) nonspecific recovery of other Mycobacterium spp. (particularly if beads were blocked with 1% skim milk before use) from broth samples containing 103 to 104 CFU/ml. When PMS was coupled with a recently optimized phage amplification assay and used to detect M. avium subsp. paratuberculosis in 50-ml volumes of spiked milk, the mean 50% limit of detection (LOD50) was 14.4 PFU/50 ml of milk (equivalent to 0.3 PFU/ml). This PMS-phage assay represents a novel, rapid method for the detection and enumeration of viable M. avium subsp. paratuberculosis organisms in milk, and potentially other sample matrices, with results available within 48 h.

Remote, subsurface detection of the algal toxin domoic acid onboard the Environmental Sample Processor: Assay development and field trials

The ability to detect harmful algal bloom (HAB) species and their toxins in real- or near real-time is a critical need for researchers studying HAB/toxin dynamics, as well as for coastal resource managers charged with monitoring bloom populations in order to mitigate their wide ranging impacts. The Environmental Sample Processor (ESP), a robotic electromechanical/fluidic system, was developed for the autonomous, subsurface application of molecular diagnostic tests and has successfully detected several HAB species using DNA probe arrays during field deployments. Since toxin production and thus the potential for public health and ecosystem effects varies considerably in natural phytoplankton populations, the concurrent detection of HAB species and their toxins onboard the ESP is essential. We describe herein the development of methods for extracting the algal toxin domoic acid (DA) from Pseudonitzschia cells (extraction efficiency >90%) and testing of samples using a competitive ELISA onboard the ESP. The assay detection limit is in the low ng/mL range (in extract), which corresponds to low ng/L levels of DA in seawater for a 0.5 L sample volume acquired by the ESP. We also report the first in situ detection of both a HAB organism (i.e., Pseudo-nitzschia) and its toxin, domoic acid, via the sequential (within 2-3 h) conduct of species- and toxin-specific assays during ESP deployments in Monterey Bay, CA, USA. Efforts are now underway to further refine the assay and conduct additional calibration exercises with the aim of obtaining more reliable, accurate estimates of bloom toxicity and thus their potential impacts. Published by Elsevier B.V.

Biosensor-based detection of reduced sex hormone-binding globulin binding capacities in response to growth-promoter administrations

Growth-promoting agents are illicitly used during animal rearing processes and the detection of their use is limited by new compounds and dosing practices that limit the efficiency of current testing which is based on residue analysis by liquid chromatography–tandem mass spectrometry (LC–MS/MS) and gas chromatography–mass spectrometry (GC–MS) methodology. An alternative approach is to use indirect biological evidence as a screening tool to identify growth-promoter treated animals thus improving the effectiveness of residue testing through the targeted sampling of these animals. Sex hormone-binding globulin (SHBG) is a glycoprotein which binds and controls the levels of sex-hormones within the circulation. Using a biosensor assay based on measurement of binding to an immobilised 1a-dihydrotestosterone (1a-DHT) derivative, reduced SHBG binding capacities were detected in growth-promoter treated animals. During the course of a veal treatment regime based on repeated oestradiol benzoate, nortestosterone decanoate and dexamethasone administrations, treated male and female calves were shown to have significantly lower SHBG capacities. To assess the effectiveness of using SHBG binding capacities as a biomarker of treatment and to investigate the role of individual growth-promoter components to the SHBG capacity lowering effects, adult heifer animals were subjected to repeated doses of nortestosterone decanoate. These animals also demonstrated a reduction in SHBG capacity levels at Day 39 of the study, in contrast to oestradiol benzoate treated adult steers who were found to have unaltered levels. These findings suggest that the measurement of SHBG binding capacities using a biosensor assay has potential in the identification of illegally treated animals, particularly those exposed to androgens.

A Pipeline Interleaved Heterogeneous SIMD Soft Processor Array Architecture for MIMO-OFDM Detection

The most promising way to maintain reliable data transfer across the rapidly fluctuating channels used by next generation multiple-input multiple-output communications schemes is to exploit run-time variable modulation and antenna configurations. This demands that the baseband signal processing architectures employed in the communications terminals must provide low cost and high performance with runtime reconfigurability. We present a softcore-processor based solution to this issue, and show for the first time, that such programmable architectures can enable real-time data operation for cutting-edge standards
such as 802.11n; furthermore, by exploiting deep processing pipelines and interleaved task execution, the cost and performance of these architectures is shown to be on a par with traditional dedicated circuit based solutions. We believe this to be the first such programmable architecture to achieve this, and the combination of implementation efficiency and programmability makes this implementation style the most promising approach for hosting such dynamic architectures.

A charged-particle microbeam .2. A single-particle micro-collimation and detection system.

The use of a charged-particle microbeam provides a unique opportunity to control precisely, the number of particles traversing individual cells and the localization of dose within the cell. The accuracy of 'aiming' and of delivering a precise number of particles crucially depends on the design and implementation of the collimation and detection system. This report describes the methods available for collimating and detecting energetic particles in the context of a radiobiological microbeam. The arrangement developed at the Gray Laboratory uses either a 'V'-groove or a thick-walled glass capillary to achieve 2-5 mu m spatial resolution. The particle detection system uses an 18 mu m thick transmission scintillator and photomultiplier tube to detect particles with >99% efficiency.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Gold-based optical biosensor for single-mismatched DNA detection using salt-induced hybridization

In this study, a gold nanoparticle (Au-NP)-based detection method for sensitive and specific DNA-based diagnostic applications is described. A sandwich format consisting of Au-NPs/DNA/PMP (Streptavidin-coated MagnetSphere Para-Magnetic Particles) was fabricated. PMPs captured and separated target DNA while Au-NPs modified with oligonucleotide detection sequences played a role in recognition and signal production. Due to the much lower stability of mismatched DNA strands caused by unstable duplex structures in solutions of relatively low salt concentration, hybridization efficiency in the presence of different buffers was well investigated, and thus, the optimized salt concentration allowed for discrimination of single-mismatched DNA (MMT) from perfectly matched DNA (PMT). Therefore, quantitative information concerning the target analyte was translated into a colorimetric signal, which could easily and quantitatively measured by low-cost UV–vis spectrophotometric analysis. The results indicated this to be a very simple and economic strategy for detection of single-mismatched DNA strands.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array. 

Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review

Background: There is growing interest in the potential utility of real-time polymerase chain reaction (PCR) in diagnosing bloodstream infection by detecting pathogen deoxyribonucleic acid (DNA) in blood samples within a few hours. SeptiFast (Roche Diagnostics GmBH, Mannheim, Germany) is a multipathogen probe-based system targeting ribosomal DNA sequences of bacteria and fungi. It detects and identifies the commonest pathogens causing bloodstream infection. As background to this study, we report a systematic review of Phase III diagnostic accuracy studies of SeptiFast, which reveals uncertainty about its likely clinical utility based on widespread evidence of deficiencies in study design and reporting with a high risk of bias. 

Objective: Determine the accuracy of SeptiFast real-time PCR for the detection of health-care-associated bloodstream infection, against standard microbiological culture. 

Design: Prospective multicentre Phase III clinical diagnostic accuracy study using the standards for the reporting of diagnostic accuracy studies criteria. 

Setting: Critical care departments within NHS hospitals in the north-west of England. 

Participants: Adult patients requiring blood culture (BC) when developing new signs of systemic inflammation. 

Main outcome measures: SeptiFast real-time PCR results at species/genus level compared with microbiological culture in association with independent adjudication of infection. Metrics of diagnostic accuracy were derived including sensitivity, specificity, likelihood ratios and predictive values, with their 95% confidence intervals (CIs). Latent class analysis was used to explore the diagnostic performance of culture as a reference standard. 

Results: Of 1006 new patient episodes of systemic inflammation in 853 patients, 922 (92%) met the inclusion criteria and provided sufficient information for analysis. Index test assay failure occurred on 69 (7%) occasions. Adult patients had been exposed to a median of 8 days (interquartile range 4–16 days) of hospital care, had high levels of organ support activities and recent antibiotic exposure. SeptiFast real-time PCR, when compared with culture-proven bloodstream infection at species/genus level, had better specificity (85.8%, 95% CI 83.3% to 88.1%) than sensitivity (50%, 95% CI 39.1% to 60.8%). When compared with pooled diagnostic metrics derived from our systematic review, our clinical study revealed lower test accuracy of SeptiFast real-time PCR, mainly as a result of low diagnostic sensitivity. There was a low prevalence of BC-proven pathogens in these patients (9.2%, 95% CI 7.4% to 11.2%) such that the post-test probabilities of both a positive (26.3%, 95% CI 19.8% to 33.7%) and a negative SeptiFast test (5.6%, 95% CI 4.1% to 7.4%) indicate the potential limitations of this technology in the diagnosis of bloodstream infection. However, latent class analysis indicates that BC has a low sensitivity, questioning its relevance as a reference test in this setting. Using this analysis approach, the sensitivity of the SeptiFast test was low but also appeared significantly better than BC. Blood samples identified as positive by either culture or SeptiFast real-time PCR were associated with a high probability (> 95%) of infection, indicating higher diagnostic rule-in utility than was apparent using conventional analyses of diagnostic accuracy. 

Conclusion: SeptiFast real-time PCR on blood samples may have rapid rule-in utility for the diagnosis of health-care-associated bloodstream infection but the lack of sensitivity is a significant limiting factor. Innovations aimed at improved diagnostic sensitivity of real-time PCR in this setting are urgently required. Future work recommendations include technology developments to improve the efficiency of pathogen DNA extraction and the capacity to detect a much broader range of pathogens and drug resistance genes and the application of new statistical approaches able to more reliably assess test performance in situation where the reference standard (e.g. blood culture in the setting of high antimicrobial use) is prone to error.