Temporal dependence of in vivo USPIO-enhanced MRI signal changes in human carotid atheromatous plaques

Introduction: Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced MRI has been shown to be a useful modality to image activated macrophages in vivo, which are principally responsible for plaque inflammation. This study determined the optimum imaging time-window to detect maximal signal change post-USPIO infusion using T1-weighted (T1w), T2*- weighted (T2*w) and quantitative T2*(qT 2*) imaging. Methods: Six patients with an asymptomatic carotid stenosis underwent high resolution T1w, T2*w and qT2*MR imaging of their carotid arteries at 1.5 T. Imaging was performed before and at 24, 36, 48, 72 and 96 h after USPIO (Sinerem™, Guerbet, France) infusion. Each slice showing atherosclerotic plaque was manually segmented into quadrants and signal changes in each quadrant were fitted to an exponential power function to model the optimum time for post-infusion imaging. Results: The power function determining the mean time to convergence for all patients was 46, 41 and 39 h for the T1w, T 2*w and qT2*sequences, respectively. When modelling each patient individually, 90% of the maximum signal intensity change was observed at 36 h for three, four and six patients on T1w, T 2*w and qT2*, respectively. The rates of signal change decrease after this period but signal change was still evident up to 96 h. Conclusion: This study showed that a suitable imaging window for T 1w, T2*w and qT2*signal changes post-USPIO infusion was between 36 and 48 h. Logistically, this would be convenient in bringing patients back for one post-contrast MRI, but validation is required in a larger cohort of patients.

Programmable digital signal averager.

A high speed digital signal averager with programmable features for the sampling period, for the number of channels and for the number of sweeps is described. The system implements a stable averaging algorithm (Deadroff and Trimble 1968) to provide a stable, calibrated display. The performance of the instrument has been evaluated for the reduction of random noise and for comb-filter action. Special uses of the instrument as a box-car integrator and as a transient recorder are also indicated.

External signal-activated liposomal drug delivery systems

Modern drug discovery gives rise to a great number of potential new therapeutic agents, but in some cases the efficient treatment of patient may not be achieved because the delivery of active compounds to the target site is insufficient. Thus, drug delivery is one of the major challenges in current pharmaceutical research. Numerous nanoparticle-based drug carriers, e.g. liposomes, have been developed for enhanced drug delivery and targeting. Drug targeting may enhance the efficiency of the treatment and, importantly, reduce unwanted side effects by decreasing drug distribution to non-target tissues. Liposomes are biocompatible lipid-based carriers that have been studied for drug delivery during the last 40 years. They can be functionalized with targeting ligands and sensing materials for triggered activation. In this study, various external signal-assisted liposomal delivery systems were developed. Signals can be used to modulate drug permeation or release from the liposome formulation, and they provide accurate control of time, place and rate of activation. The study involved three types of signals that were used to trigger drug permeation and release: electricity, heat and light. Electrical stimulus was utilized to enhance the permeation of liposomal DNA across the skin. Liposome/DNA complex-mediated transfections were performed in tight rat epidermal cell model. Various transfection media and current intensities were tested, and transfection efficiency was evaluated non-invasively by monitoring the concentration of secreted reporter protein in cell culture medium. Liposome/DNA complexes produced gene expression, but electrical stimulus did not enhance the transfection efficiency significantly. Heat-sensitive liposomal drug delivery system was developed by coating liposomes with biodegradable and thermosensitive poly(N-(2-hydroxypropyl) methacrylamide-mono/dilactate polymer. Temperature-triggered liposome aggregation and contents release from liposomes were evaluated. The cloud point temperature (CP) of the polymer was set to 42 °C. Polymer-coated liposome aggregation and contents release were observed above CP of the polymer, while non-coated liposomes remained intact. Polymer precipitates above its CP and interacts with liposomal bilayers. It is likely that this induces permeabilization of the liposomal membrane and contents release. Light-sensitivity was introduced to liposomes by incorporation of small (< 5 nm) gold nanoparticles. Hydrophobic and hydrophilic gold nanoparticles were embedded in thermosensitive liposomes, and contents release was investigated upon UV light exposure. UV light-induced lipid phase transitions were examined with small angle X-ray scattering, and light-triggered contents release was shown also in human retinal pigment epithelial cell line. Gold nanoparticles absorb light energy and transfer it into heat, which induces phase transitions in liposomes and triggers the contents release. In conclusion, external signal-activated liposomes offer an advanced platform for numerous applications in drug delivery, particularly in the localized drug delivery. Drug release may be localized to the target site with triggering stimulus that results in better therapeutic response and less adverse effects. Triggering signal and mechanism of activation can be selected according to a specific application.

Non-stationary signal analysis by least mean fourth (LMF) adaptive algorithm

A modified least mean fourth (LMF) adaptive algorithm applicable to non-stationary signals is presented. The performance of the proposed algorithm is studied by simulation for non-stationarities in bandwidth, centre frequency and gain of a stochastic signal. These non-stationarities are in the form of linear, sinusoidal and jump variations of the parameters. The proposed LMF adaptation is found to have better parameter tracking capability than the LMS adaptation for the same speed of convergence.

Comments and Correspondence on a programmable digital signal averager

In a recent paper, Srinivasan et al (1980) have described a programmable digital signal averager with facility for programming the sampling period, number of channels and number of sweeps. We have examined this paper in some detail and find that some points need clarification.

Simplified algorithms based on Haar transforms for signal recognition in protective relays

This letter presents the development of simplified algorithms based on Haar functions for signal extraction in relaying signals. These algorithms, being computationally simple, are better suited for microprocessor-based power system protection relaying. They provide accurate estimates of the signal amplitude and phase.

Prolonged hyperinsulinemia affects metabolic signal transduction markers in a tissue specific manner

Insulin dysregulation is common in horses although the mechanisms of metabolic dysfunction are poorly understood. We hypothesized that insulin signaling in striated (cardiac and skeletal) muscle and lamellae may be mediated through different receptors as a result of receptor content, and that transcriptional regulation of downstream signal transduction and glucose transport may also differ between tissues sites during hyperinsulinemia. Archived samples from horses treated with a prolonged insulin infusion or a balanced electrolyte solution were used. All treated horses developed marked hyperinsulinemia and clinical laminitis. Protein expression was compared across tissues for the insulin receptor and insulin-like growth factor 1 receptor (IGF-1R) by immunoblotting. Gene expression of metabolic insulin-signaling markers (insulin receptor substrate 1, Akt2, and glycogen synthase kinase 3 beta [GSK-3β]) and glucose transport (basal glucose transporter 1 and insulin-sensitive glucose transporter 4) was evaluated using real-time reverse transcription polymerase chain reaction. Lamellar tissue contained significantly more IGF-1R protein than skeletal muscle, indicating the potential significance of IGF-1R signaling for this tissue. Gene expression of the selected markers of insulin signaling and glucose transport in skeletal muscle and lamellar tissues was unaffected by prolonged hyperinsulinemia. In contrast, the significant upregulation of Akt2, GSK-3β, GLUT1, and GLUT4 gene expression in cardiac tissue suggested that the prolonged hyperinsulinemia induced an increase in insulin sensitivity and a transcriptional activation of glucose transport. Responses to insulin are tissue-specific, and extrapolation of data across tissue sites is inappropriate.

Signal Characterization using Fractal Dimension

Fractal Dimensions (FD) are popular metrics for characterizing signals. They are used as complexity measuresin signal analysis applications in various fields. However, proper interpretation of such analyses has not been thoroughly addressed. In this paper, we study the effect of various signal properties on FD and interpret results in terms of classical signal processing concepts such as amplitude, frequency,number of harmonics, noise power and signal bandwidth. We have used Higuchi’s method for estimating FDs. This study helps in gaining a better understanding of the FD complexity measure for various signal parameters. Our results indicate that FD is a useful metric in estimating various signal properties. As an application of the FD measure in real world scenario, the FD is used as a feature in discriminating seizures from seizure free intervals in intracranial EEG data recordings and the FD feature has given good discrimination performance.

Spectral Sensing for Cognitive Radio: Estimation of Adaptive Frequency Hopping Signal

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Effect of Crowding Agents, Signal Peptide, and Chaperone SecB on the Folding and Aggregation of E. coli Maltose Binding Protein

SecB, a soluble cytosolic chaperone component of the Secexport pathway, binds to newly synthesized precursor proteins and prevents their premature aggregation and folding and subsequently targets them to the translocation machinery on the membrane. PreMBP, the precursor form of maltose binding protein, has a 26-residue signal sequence attached to the N-terminus of MBP and is a physiological substrate of SecB. We examine the effect of macromolecular crowding and SecB on the stability and refolding of denatured preMBP and MBP. PreMBP was less stable than MBP (ΔTm =7( 0.5 K) in both crowded and uncrowded solutions. Crowding did not cause any substantial changes in the thermal stability ofMBP(ΔTm=1(0.4 K) or preMBP (ΔTm=0(0.6 K), as observed in spectroscopically monitored thermal unfolding experiments. However, both MBP and preMBP were prone to aggregation while refolding under crowded conditions. In contrast to MBP aggregates, which were amorphous, preMBP aggregates form amyloid fibrils.Under uncrowded conditions, a molar excess of SecB was able to completely prevent aggregation and promote disaggregation of preformed aggregates of MBP. When a complex of the denatured protein and SecB was preformed, SecB could completely prevent aggregation and promote folding of MBP and preMBP even in crowded solution. Thus, in addition to maintaining substrates in an unfolded, export-competent conformation, SecB also suppresses the aggregation of its substrates in the crowded intracellular environment. SecB is also able to promote passive disaggregation of macroscopic aggregates of MBP in the absence of an energy source such as ATP or additional cofactors. These experiments also demonstrate that signal peptide can reatly influence protein stability and aggregation propensity.

The Mechanisms of Hedgehog Signal Transduction

Studies in both vertebrates and invertebrates have identified proteins of the Hedgehog (Hh) family of secreted signaling molecules as key organizers of tissue patterning. Initially discovered in Drosophila in 1992, Hh family members have been discovered in animals with body plans as diverse as those of mammals, insects and echinoderms. In humans three related Hh genes have been identified: Sonic, Indian and Desert hedgehog (Shh, Ihh and Dhh). Transduction of the Hh signal to the cytoplasm utilizes an unusual mechanism involving consecutive repressive interactions between Hh and its receptor components, Patched (Ptc) and Smoothened (Smo). Several cytoplasmic proteins involved in Hh signal transduction are known in Drosophila, but mammalian homologs are known only for the Cubitus interruptus (Ci) transcription factor (GLI(1-3)) and for the Ci/GLI-associated protein, Suppressor of Fused (Su(fu)). In this study I analyzed the mechanisms of how the Hh receptor Ptc regulates the signal transducer Smo, and how Smo relays the Shh signal from the cell surface to the cytoplasm ultimately leading to the activation of GLI transcription factors. In Drosophila, the kinesin-like protein Costal2 (Cos2) is required for suppression of Hh target gene expression in the absence of ligand, and loss of Cos2 causes embryonic lethality. Cos2 acts by bridging Smo to the Ci. Another protein, Su(Fu) exerts a weak suppressive influence on Ci activity and loss of Su(Fu) causes subtle changes in Drosophila wing pattern. This study revealed that domains in Smo that are critical for Cos2 binding in Drosophila are dispensable for mammalian Smo function. Furthermore, by analyzing the function of Su(Fu) and the closest mouse homologs of Cos2 by protein overexpression and RNA interference I found that inhibition of the Hh response pathway in the absence of ligand does not require Cos2 activity, but instead critically depends on the activity of Su(Fu). These results indicate that a major change in the mechanism of action of a conserved signaling pathway occurred during evolution, probably through phenotypic drift made possible by the existence in some species of two parallel pathways acting between the Hh receptor and the Ci/GLI transcription factors. In a second approach to unravel Hh signaling we cloned > 90% of all human full-length protein kinase cDNAs and constructed the corresponding kinase-activity deficient mutants. Using this kinome resource as a screening tool, two kinases, MAP3K10 and DYRK2 were found to regulate Shh signaling. DYRK2 directly phosphorylated and induced the proteasome dependent degradation of the key Hh-pathway regulated transcription factor, GLI2. MAP3K10, in turn, affected GLI2 indirectly by modulating the activity of DYRK2.

Short- and long-term movement patterns in the freshwater whipray (Himantura dalyensis) determined by the signal processing of passive acoustic telemetry data.

Patterns of movement in aquatic animals reflect ecologically important behaviours. Cyclical changes in the abiotic environment influence these movements, but when multiple processes occur simultaneously, identifying which is responsible for the observed movement can be complex. Here we used acoustic telemetry and signal processing to define the abiotic processes responsible for movement patterns in freshwater whiprays (Himantura dalyensis). Acoustic transmitters were implanted into the whiprays and their movements detected over 12 months by an array of passive acoustic receivers, deployed throughout 64 km of the Wenlock River, Qld, Australia. The time of an individual's arrival and departure from each receiver detection field was used to estimate whipray location continuously throughout the study. This created a linear-movement-waveform for each whipray and signal processing revealed periodic components within the waveform. Correlation of movement periodograms with those from abiotic processes categorically illustrated that the diel cycle dominated the pattern of whipray movement during the wet season, whereas tidal and lunar cycles dominated during the dry season. The study methodology represents a valuable tool for objectively defining the relationship between abiotic processes and the movement patterns of free-ranging aquatic animals and is particularly expedient when periods of no detection exist within the animal location data.

'A programmable digital signal averager' Reply

In a recent paper, Srinivasan et al (1980) have described a programmable digital signal averager with facility for programming the sampling period, number of channels and number of sweeps. We have examined this paper in some detail and find that some points need clarification.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.