Quantitative stem-loop RT-PCR for detection of microRNAs

Plant microRNAs (miRNAs) are a class of endogenous small RNAs that are essential for plant development and survival. They arise from larger precursor RNAs with a characteristic hairpin structure and regulate gene activity by targeting mRNA transcripts for cleavage or translational repression. Efficient and reliable detection and quantification of miRNA expression has become an essential step in understanding their specific roles. The expression levels of miRNAs can vary dramatically between samples and they often escape detection by conventional technologies such as cloning, northern hybridization and microarray analysis. The stem-loop RT-PCR method described here is designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. First, a miRNA-specific stem-loop RT primer is hybridized to the miRNA and then reverse transcribed. Next, the RT product is amplified and monitored in real time using a miRNA-specific forward primer and the universal reverse primer. This method enables miRNA expression profiling from as little as 10 pg of total RNA and is suitable for high-throughput miRNA expression analysis.

Correlation between extent of osteolytic damage and metastatic burden of human breast cancer metastasis in nude mice : real-time PCR quantitation

Orthotopic or intracardiac injection of human breast cancer cell lines into immunocompromised mice allows study of the molecular basis of breast cancer metastasis. We have established a quantitative real-time PCR approach to analyze metastatic spread of human breast cancer cells inoculated into nude mice via these routes. We employed MDA-MB-231 human breast cancer cells genetically tagged with a bacterial β-galactosidase (Lac-Z) retroviral vector, enabling their detection by TaqMan® real-time PCR. PCR detection was linear, specific, more sensitive than conventional PCR, and could be used to directly quantitate metastatic burden in bone and soft organs. Attesting to the sensitivity and specificity of the PCR detection strategy, as few as several hundred metastatic MDA-MB-231 cells were detectable in 100 μm segments of paraffin-embedded lung tissue, and only in samples adjacent to sections that scored positive by histological detection. Moreover, the measured real-time PCR metastatic burden in the bone environment (mouse hind-limbs, n = 48) displayed a high correlation to the degree of osteolytic damage observed by high resolution X-ray analysis (r2 = 0.972). Such a direct linear relationship to tumor burden and bone damage substantiates the so-called 'vicious cycle' hypothesis in which metastatic tumor cells promote the release of factors from the bone which continue to stimulate the tumor cells. The technique provides a useful tool for molecular and cellular analysis of human breast cancer metastasis to bone and soft organs, can easily be extended to other cell/marker/organ systems, and should also find application in preclinical assessment of anti-metastatic modalities.

Analysis of unsaturated lipids by ozone-induced dissociation

Recent developments in analytical technologies have driven significant advances in lipid science. The sensitivity and selectivity of modern mass spectrometers can now provide for the detection and even quantification of many hundreds of lipids in a single analysis. In parallel, increasing evidence from structural biology suggests that a detailed knowledge of lipid molecular structure including carbon-carbon double bond position, stereochemistry and acyl chain regiochemistry is required to fully appreciate the biochemical role(s) of individual lipids. Here we review the capabilities and limitations of tandem mass spectrometry to provide this level of structural specificity in the analysis of lipids present in complex biological extracts. In particular, we focus on the capabilities of a novel technology termed ozone-induced dissociation to identify the position (s) of double bonds in unsaturated lipids and discuss its possible role in efforts to develop workflows that provide for complete structure elucidation of lipids by mass spectrometry alone: so-called top-down lipidomics. This article is part of a Special Issue entitled: Lipodomics and Imaging Mass Spectrom. (C) 2011 Elsevier B.V. All rights reserved.

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

Accelerometer validity and placement for detection of changes in physical activity in dogs under controlled conditions on a treadmill

The objective of the research was to determine the optimal location and method of attachment for accelerometer-based motion sensors, and to validate their ability to differentiate rest and increases in speed in healthy dogs moving on a treadmill. Two accelerometers were placed on a harness between the scapulae of dogs with one in a pouch and one directly attached to the harness. Two additional accelerometers were placed (pouched and not pouched) ventrally on the dog's collar. Data were recorded in 1. s epochs with dogs moving in stages lasting 3. min each on a treadmill: (1) at rest, lateral recumbency, (2) treadmill at 0% slope, 3. km/h, (3) treadmill at 0% slope, 5. km/h, (4) treadmill at 0% slope, 7. km/h, (5) treadmill at 5% slope, 5. km/h, and; (6) treadmill at 5% slope, 7. km/h. Only the harness with the accelerometer in a pouch along the dorsal midline yielded statistically significant increases (P< 0.05) in vector magnitude as walking speed of the dogs increased (5-7. km/h) while on the treadmill. Statistically significant increases in vector magnitude were detected in the dogs as the walking speed increased from 5 to 7. km/h, however, changes in vector magnitude were not detected when activity intensity was increased as a result of walking up a 5% grade. Accelerometers are a valid and objective tool able to discriminate between and monitor different levels of activity in dogs in terms of speed of movement but not in energy expenditure that occurs with movement up hill.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

lacZ transduced human breast cancer xenografts as an in vivo model for the study of invasion and metastasis

A number of human cancer cell lines have been described as being invasive and metastatic in immune incompetent animals. However, it is difficult to assess metastatic spread of a subcutaneously injected or inoculated cell line, since an exact detection of all microfoci of human tumour cells in the animals by usual histological procedures would require extensive sectioning of the whole animal. To overcome this problem, we transduced human breast cancer cells with a replication-defective Moloney murine leukaemia retroviral vector (M-MuLV) containing both neo(R) (neomycin resistance) and lacZ genes. The resulting cell lines were selected for antibiotic (G418) resistance, and cell-sorted for lacZ expression. lacZ continued to be expressed in cultured cells for at least 20 passages without further G418 selection. The lacE gene codes for β-D-galactosidase, and cells expressing this gene stain blue with the chromogenic substrate X-gal. The lacZ-expressing cells retained the pre-transduction ability to traverse Matrigel in vitro, to form subcutaneous tumours in nude mice, and to grow invasively with the formation of metastases. X-gal staining showed high specificity, staining the tumour cells but not the surrounding mouse tissue on either whole tissue blocks or histological sections. The staining procedure was highly sensitive, allowing detection of microfoci of human cancer cells, and quantitative estimation of the metastatic capacity of the cells. These results indicate that lacZ transduction of human tumour cells is a powerful means of studying human cancer cell invasion and metastases in vivo.

A novel identification method for ultra trace detection of biomolecules using functionalised Surface Enhanced Raman Spectroscopy (SERS)

This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.

Detection of object onset and offset in naturalistic scenes

The present study was conducted to investigate whether ob- servers are equally prone to overlook any kinds of visual events in change blindness. Capitalizing on the finding from visual search studies that abrupt appearance of an object effectively captures observers' attention, the onset of a new object and the offset of an existing object were contrasted regarding their detectability when they occurred in a naturalistic scene. In an experiment, participants viewed a series of photograph pairs in which layouts of seven or eight objects were depicted. One object either appeared in or disappeared from the layout, and participants tried to detect this change. Results showed that onsets were detected more quickly than offsets, while they were detected with equivalent ac- curacy. This suggests that the primacy of onset over offset is a robust phenomenon that likely makes onsets more resistant to change blindness under natural viewing conditions.

Nucleic acid hybridizations as radioactive tool for rapid detection of banana bunchy top virus

Banana bunchy top disease (BBTD) caused by banana bunchy top virus (BBTV) was radioactively detected by nucleic acid hybridization techniques. Results showed that, 32P-labelled insert of pBT338 was hybridized with nucleic acid extracts from BBTV-infected plants from Egypt and Australia but not with those from CMV-infected plants from Egypt. Results revealed that BBTV was greatly detected in midrib, roots, meristem, corm, leaves and pseudostem respectively. BBTV was also detected in symptomless young plants prepared from diseased plant materials grown under tissue culture conditions but was not present in those performed from healthy plant materials. The sensitivity of dot blot and Southern blot hybridizations for the detection of BBTV was also performed for the detection of BBTV.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

Plasma-enabled graded nanotube biosensing arrays on a Si nanodevice platform : catalyst-free integration and in situ detection of nucleation events

Low-temperature plasmas in direct contact with arbitrary, written linear features on a Si wafer enable catalyst-free integration of carbon nanotubes into a Si-based nanodevice platform and in situ resolution of individual nucleation events. The graded nanotube arrays show reliable, reproducible, and competitive performance in electron field emission and biosensing nanodevices.

Asymptotic minimax robust and misspecified Lorden quickest change detection for dependent stochastic processes

The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Telomerase activity : detection and clinical implications in human cancer

Telomerase is an extremely important enzyme required for the immortalisation of tumour cells. Because the gene is activated in the vast majority of tumour tissues and remains unused in most somatic cells, it represents a marker with huge diagnostic, prognostic and treatment implications in cancer. This article summarises the basic structure and functions of telomerase and considers its clinical implications in colorectal and other cancers.