The use of artificial MicroRNA technology to control gene expression in Arabidopsis thaliana

In plants, double-stranded RNA (dsRNA) is an effective trigger of RNA silencing, and several classes of endogenous small RNA (sRNA), processed from dsRNA substrates by DICER-like (DCL) endonucleases, are essential in controlling gene expression. One such sRNA class, the microRNAs (miRNAs) control the expression of closely related genes to regulate all aspects of plant development, including the determination of leaf shape, leaf polarity, flowering time, and floral identity. A single miRNA sRNA silencing signal is processed from a long precursor transcript of nonprotein-coding RNA, termed the primary miRNA (pri-miRNA). A region of the pri-miRNA is partially self-complementary allowing the transcript to fold back onto itself to form a stem-loop structure of imperfectly dsRNA. Artificial miRNA (amiRNA) technology uses endogenous pri-miRNAs, in which the miRNA and miRNA*(passenger strand of the miRNA duplex) sequences have been replaced with corresponding amiRNA/ amiRNA*sequences that direct highly efficient RNA silencing of the targeted gene. Here, we describe the rules for amiRNA design, as well as outline the PCR and bacterial cloning procedures involved in the construction of an amiRNA plant expression vector to control target gene expression in Arabidopsis thaliana. © 2014 Springer Science+Business Media New York.

Efficient silencing of endogenous microRNAs using artificial microRNAs in Arabidopsis thaliana

We report here that the expression of endogenous microRNAs (miRNAs) can be efficiently silenced in Arabidopsis thaliana (Arabidopsis) using artificial miRNA (amiRNA) technology. We demonstrate that an amiRNA designed to target a mature miRNA directs silencing against all miRNA family members, whereas an amiRNA designed to target the stem-loop region of a miRNA precursor transcript directs silencing against only the individual family member targeted. Furthermore, our results indicate that amiRNAs targeting both the mature miRNA and stem-loop sequence direct RNA silencing through cleavage of the miRNA precursor transcript, which presumably occurs in the nucleus of a plant cell during the initial stages of miRNA biogenesis. This suggests that small RNA (sRNA)-guided RNA cleavage in plants occurs not only in the cytoplasm, but also in the nucleus. Many plant miRNA gene families have been identified via sequencing and bioinformatic analysis, but, to date, only a small tranche of these have been functionally characterized due to a lack of effective forward or reverse genetic tools. Our findings therefore provide a new and powerful reverse-genetic tool for the analysis of miRNA function in plants. © The Author 2010. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS.

Cloning and characterization of microRNAs from Brassica napus

A library containing approximately 40,000 small RNA sequences was constructed for Brassica napus. Analysis of 3025 sequences obtained from this library resulted in the identification of 11 conserved miRNA families, which were validated by secondary structure prediction using surrounding sequences in the Brassica genome. Two 21 nt small RNA sequences reside within the arm of a pre-miRNA like stem-loop structure, making them likely candidates for novel non-conserved miRNAs in B. napus. Most of the conserved miRNAs were expressed at similar levels in a F1 hybrid B. napus line and its four double haploid progeny that showed marked variations in phenotypes, but many were differentially expressed between B. napus and Arabidopsis. The miR169 family was expressed at high levels in young leaves and stems, but was undetectable in roots and mature leaves, suggesting that miR169 expression is developmentally regulated in B. napus. © 2007 Federation of European Biochemical Societies.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

A systemic view of innovation adoption in the Australian beef industry

Significant investments in developing technological innovations have been made in the Australian beef industry but with low adoption rates. By modelling the key variables and their interactions in the innovation adoption process, this research seeks to demonstrate the complexity and dynamics of the process. This research uses causal loop modelling and develops a holistic model of the current innovation adoption system in the Australian beef industry to show the complexity of dynamic interactions among multiple variables. It is suggested that innovation adoption is such an extremely complex issue, and we need to shift our views on this issue from a paradigm of linear thinking to systems thinking. Innovation adoption is more likely to be enhanced based on a full understanding of the complexity and dynamics of the system as a whole. The paper demonstrates to practitioners and developers of innovation the multiple variables and interactions impacting innovation adoption.

Hybrid model for motorway travel time estimation considering increased detector spacing

Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.

RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

Can we text you? A qualitative exploration of young unemployed job-seekers’ attitudes to receiving resilience-building SMS messages

A significant minority of young job-seekers remain unemployed for many months, and are at risk of developing depression. Both empirical studies and theoretical models suggest that cognitive, behavioural and social isolation factors interact to increase this risk. Thus, interventions that reduce or prevent depression in young unemployed job-seekers by boosting their resilience are required. Mobile phones may be an effective medium to deliver resilience-boosting support to young unemployed people by using SMS messages to interrupt the feedback loop of depression and social isolation. Three focus groups were conducted to explore young unemployed job-seekers’ attitudes to receiving and requesting regular SMS messages that would help them to feel supported and motivated while job-seeking. Participants reacted favourably to this proposal, and thought that it would be useful to continue to receive and request SMS messages for a few months after commencing employment as well.

Structures of μOconotoxins from Conusmarmoreus. Inhibitors of tetrodotoxin (TTX)-sensitive and TTX-resistant sodium channels in mammalian sensory neurons

The μO-conotoxins are an intriguing class of conotoxins targeting various voltage-dependent sodium channels and molluscan calcium channels. In the current study, we have shown MrVIA and MrVIB to be the first known peptidic inhibitors of the transient tetrodotoxin-resistant (TTX-R) Na+ current in rat dorsal root ganglion neurons, in addition to inhibiting tetrodotoxin-sensitive Na+ currents. Human TTX-R sodium channels are a therapeutic target for indications such as pain, highlighting the importance of the μO-conotoxins as potential leads for drug development. Furthermore, we have used NMR spectroscopy to provide the first structural information on this class of conotoxins. MrVIA and MrVIB are hydrophobic peptides that aggregate in aqueous solution but were solubilized in 50% acetonitrile/water. The three-dimensional structure of MrVIB consists of a small β-sheet and a cystine knot arrangement of the three-disulfide bonds. It contains four backbone “loops” between successive cysteine residues that are exposed to the solvent to varying degrees. The largest of these, loop 2, is the most disordered part of the molecule, most likely due to flexibility in solution. This disorder is the most striking difference between the structures of MrVIB and the known δ- and ω-conotoxins, which along with the μO-conotoxins are members of the O superfamily. Loop 2 of ω-conotoxins has previously been shown to contain residues critical for binding to voltage-gated calcium channels, and it is interesting to speculate that the flexibility observed in MrVIB may accommodate binding to both sodium and molluscan calcium channels.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

The mitochondrial genome of the Russian wheat aphid Diuraphis noxia : large repetitive sequences between trnE and trnF in aphids

To characterize aphid mitochondrial genome (mitogenome) features, we sequenced the complete mitogenome of the Russian wheat aphid, Diuraphis noxia. The 15,784-bp mitogenome with a high A + T content (84.76%) and strong C skew (− 0.26) was arranged in the same gene order as that of the ancestral insect. Unlike typical insect mitogenomes, D. noxia possessed a large tandem repeat region (644 bp) located between trnE and trnF. Sequencing partial mitogenome of the cotton aphid (Aphis gossypii) further confirmed the presence of the large repeat region in aphids, but with different repeat length and copy number. Another motif (58 bp) tandemly repeated 2.3 times in the control region of D. noxia. All repeat units in D. noxia could be folded into stem-loop secondary structures, which could further promote an increase in copy numbers. Characterization of the D. noxia mitogenome revealed distinct mitogenome architectures, thus advancing our understanding of insect mitogenomic diversities and evolution.

The osteogenic transcription factor Runx2 regulates components of the fibroblast growth factor/proteoglycan signaling axis in osteoblasts

Heparan sulfate proteoglycans cooperate with basic fibroblast growth factor (bFGF/FGF2) signaling to control osteoblast growth and differentiation, as well as metabolic functions of osteoblasts. FGF2 signaling modulates the expression and activity of Runt-related transcription factor 2 (Runx2/Cbfa1), a key regulator of osteoblast proliferation and maturation. Here, we have characterized novel Runx2 target genes in osteoprogenitors under conditions that promote growth arrest while not yet permitting sustained phenotypic maturation. Runx2 enhances expression of genes related to proteoglycan-mediated signaling, including FGF receptors (e.g., FGFR2 and FGFR3) and proteoglycans (e.g., syndecans [Sdc1, Sdc2, Sdc3], glypicans [Gpc1], versican [Vcan]). Runx2 increases expression of the glycosyltransferase Exostosin-1 (Ext1) and heparanase, as well as alters the relative expression of N-linked sulfotransferases (Ndst1 = Ndst2 > Ndst3) and enzymes mediating O-linked sulfation of heparan sulfate (Hs2st > Hs6st) or chondroitin sulfate (Cs4st > Cs6st). Runx2 cooperates with FGF2 to induce expression of Sdc4 and the sulfatase Galns, but Runx2 and FGF2 suppress Gpc6, thus suggesting intricate Runx2 and FGF2 dependent changes in proteoglycan utilization. One functional consequence of Runx2 mediated modulations in proteoglycan-related gene expression is a change in the responsiveness of bone markers to FGF2 stimulation. Runx2 and FGF2 synergistically enhance osteopontin expression (>100 fold), while FGF2 blocks Runx2 induction of alkaline phosphatase. Our data suggest that Runx2 and the FGF/proteoglycan axis may form an extracellular matrix (ECM)-related regulatory feed-back loop that controls osteoblast proliferation and execution of the osteogenic program.

Constrained control design for dynamic positioning of marine vehicles with control allocation

In this paper, we address the control design problem of positioning of over-actuated marine vehicles with control allocation. The proposed design is based on a combined position and velocity loops in a multi-variable anti-windup implementation together with a control allocation mapping. The vehicle modelling is considered with appropriate simplifications related to low-speed manoeuvring hydrodynamics and vehicle symmetry. The control design is considered together with a control allocation mapping. We derive analytical tuning rules based on requirements of closed-loop stability and performance. The anti- windup implementation of the controller is obtained by mapping the actuator-force constraint set into a constraint set for the generalized forces. This approach ensures that actuation capacity is not violated by constraining the generalized control forces; thus, the control allocation is simplified since it can be formulated as an unconstrained problem. The mapping can also be modified on-line based on actuator availability to provide actuator-failure accommodation. We provide a proof of the closed-loop stability and illustrate the performance using simulation scenarios for an open-frame underwater vehicle.

Resection-intersection bundle adjustment revisited

Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation; only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.

Improving the performance of nutrition screening through a series of quality improvement initiatives

Background Nutrition screening identifies patients at risk of malnutrition to facilitate early nutritional intervention. Studies have reported incompletion and error rates of 30-90% for a range of commonly used screening tools. This study aims to investigate the incompletion and error rates of 3-Minute Nutrition Screening (3-MinNS) and the effect of quality improvement initiatives in improving the overall performance of the screening tool and the referral process for at risk patients. Methods Annual audits were carried out from 2008-2013 on 4467 patients. Value Stream Mapping, Plan-Do-Check-Act cycle and Root Cause Analysis were used in this study to identify gaps and determine the best intervention. The intervention included 1) implementing a nutrition screening protocol, 2) nutrition screening training, 3) nurse empowerment for online dietetics referral of at-risk cases, 4) closed-loop feedback system and 5) removing a component of 3-MinNS that caused the most error without compromising its sensitivity and specificity. Results Nutrition screening error rates were 33% and 31%, with 5% and 8% blank or missing forms, in 2008 and 2009 respectively. For patients at risk of malnutrition, referral to dietetics took up to 7.5 days, with 10% not referred at all. After intervention, the latter decreased to 7% (2010), 4% (2011) and 3% (2012 and 2013), and the mean turnaround time from screening to referral was reduced significantly from 4.3 ± 1.8 days to 0.3 ± 0.4 days (p < 0.001). Error rates were reduced to 25% (2010), 15% (2011), 7% (2012) and 5% (2013) and percentage of blank or missing forms reduced to and remained at 1%. Conclusion Quality improvement initiatives are effective in reducing the incompletion and error rates of nutrition screening, and led to sustainable improvements in the referral process of patients at nutritional risk.