The role of prior exposure on the capture of attention by items in working memory

The Biased Competition Model (BCM) suggests both top-down and bottom-up biases operate on selective attention (e.g., Desimone & Duncan, 1995). It has been suggested that top-down control signals may arise from working memory. In support, Downing (2000) found faster responses to probes presented in the location of stimuli held vs. not held in working memory. Soto, Heinke, Humphreys, and Blanco (2005) showed the involuntary nature of this effect and that shared features between stimuli were sufficient to attract attention. Here we show that stimuli held in working memory had an influence on the deployment of attentional resources even when: (1) It was detrimental to the task, (2) there was equal prior exposure, and (3) there was no bottom-up priming. These results provide further support for involuntary top-down guidance of attention from working memory and the basic tenets of the BCM, but further discredit the notion that bottom-up priming is necessary for the effect to occur.

Acanthamoeba polyphaga trophozoite binding of representative fungal single cell forms

Acanthamoeba polyphaga trophozoites bind yeast cells of Candida albicans isolates within a few hours, leaving few cells in suspension or still attached to trophozoite surfaces. The nature of yeast cell recognition, mediated by an acanthamoebal trophozoite mannose binding protein is confirmed by experiments utilizing concentration dependent mannose hapten blocking. Similarly, acapsulate cells of Cryptococcus neoformans are also bound within a relatively short timescale. However, even after protracted incubation many capsulate cells of Cryptococcus remain in suspension, suggesting that the capsulate cell form of this species is not predated by acanthamoebal trophozoites. Further aspects of the association of Acanthamoeba and fungi are apparent when studying their interaction with conidia of the biocontrol agent Coniothyrium minitans. Conidia which readily bind with increasing maturity of up to 42 days, were little endocytosed and even released. Cell and conidial surface mannose as determined by FITC-lectin binding, flow cytometry with associated ligand binding analysis and hapten blocking studies demonstrates the following phenomena. Candida isolates and acapsulate Cryptococcus expose most mannose, while capsulate Cryptococcus cells exhibit least exposure commensurate with yeast cellular binding or lack of trophozoites. Conidia of Coniothyrium, albeit in a localized fashion, also manifest surface mannose exposure but as shown by Bmax values, in decreasing amounts with increasing maturity. Contrastingly such conidia experience greater trophozoite binding with maturation, thereby questioning the primacy of a trophozoite mannose-binding-protein recognition model.

Time for action? Elementary engineering education - Challenging teachers, policy makers and parents

Grounded in the findings of a three year exploratory student whereby teachers' and policy makers' perceptions of elementary level engineering education were analysed, this paper focuses upon three strands of engineering education activity: Pedagogy: Practice, and: Policy. Taking into account the challenges associated with introducing engineering education at an elementary level across the UK, the paper critiques the role played by the 'competition model' in promoting engineering to children and 4 to 11 years. In considering the 'added value' that appropriately developed engineering education activities can offer in the classroom the discussion argues that elementary level engineering has the potential to reach across the curriculum, offering context and depth in many different areas. The paper concludes by arguing that by introducing the discipline to children at a foundational level, switching on their 'Engineering Imaginations' and getting them to experience the value and excitement of engineering, maths and applied science a new "Educational Frontier" will be forged. © American Society for Engineering Education, 2014.

Developing a scalable model of recombinant protein yield from Pichia pastoris:the influence of culture conditions, biomass and induction regime

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

Expression of the human cachexia-associated protein (HCAP) in prostate cancer and in a prostate cancer animal model of cachexia

Prostate cancer (CaP) patients with disseminated disease often suffer from severe cachexia, which contributes to mortality in advanced cancer. Human cachexia-associated protein (HCAP) was recently identified from a breast cancer library based on the available 20-amino acid sequence of proteolysis-inducing factor (PIF), which is a highly active cachectic factor isolated from mouse colon adenocarcinoma MAC16. Herein, we investigated the expression of HCAP in CaP and its potential involvement in CaP-associated cachexia. HCAP mRNA was detected in CaP cell lines, in primary CaP tissues and in its osseous metastases. In situ hybridization showed HCAP mRNA to be localized only in the epithelial cells in CaP tissues, in the metastatic foci in bone, liver and lymph node, but not in the stromal cells or in normal prostate tissues. HCAP protein was detected in 9 of 14 CaP metastases but not in normal prostate tissues from cadaveric donors or patients with organ-confined tumors. Our Western blot analysis revealed that HCAP was present in 9 of 19 urine specimens from cachectic CaP patients but not in 19 urine samples of noncachectic patients. HCAP mRNA and protein were also detected in LuCaP 35 and PC-3M xenografts from our cachectic animal models. Our results demonstrated that human CaP cells express HCAP and the expression of HCAP is associated with the progression of CaP and the development of CaP cachexia. © 2003 Wiley-Liss, Inc.

Development of an in-vitro model system to investigate the mechanism of muscle protein catabolism induced by proteolysis-inducing factor

The mechanism of muscle protein catabolism induced by proteolysis-inducing factor, produced by cachexia-inducing murine and human tumours has been studied in vitro using C2C12 myoblasts and myotubes. In both myoblasts and myotubes protein degradation was enhanced by proteolysis-inducing factor after 24 h incubation. In myoblasts this followed a bell-shaped dose-response curve with maximal effects at a proteolysis-inducing factor concentration between 2 and 4 nM, while in myotubes increased protein degradation was seen at all concentrations of proteolysis-inducing factor up to 10 nM, again with a maximum of 4 nM proteolysis-inducing factor. Protein degradation induced by proteolysis-inducing factor was completely attenuated in the presence of cycloheximide (1 μM), suggesting a requirement for new protein synthesis. In both myoblasts and myotubes protein degradation was accompanied by an increased expression of the α-type subunits of the 20S proteasome as well as functional activity of the proteasome, as determined by the 'chymotrypsin-like' enzyme activity. There was also an increased expression of the 19S regulatory complex as well as the ubiquitin-conjugating enzyme (E214k), and in myotubes a decrease in myosin expression was seen with increasing concentrations of proteolysis-inducing factor. These results show that proteolysis-inducing factor co-ordinately upregulates both ubiquitin conjugation and proteasome activity in both myoblasts and myotubes and may play an important role in the muscle wasting seen in cancer cachexia. © 2002 Cancer Research UK.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

Attenuation of muscle atrophy in a murine model of cachexia by inhibition of the dsRNA-dependent protein kinase

Atrophy of skeletal muscle is due to a depression in protein synthesis and an increase in degradation. Studies in vitro have suggested that activation of the dsRNA-dependent protein kinase (PKR) may be responsible for these changes in protein synthesis and degradation. In order to evaluate whether this is also applicable to cancer cachexia the action of a PKR inhibitor on the development of cachexia has been studied in mice bearing the MAC16 tumour. Treatment of animals with the PKR inhibitor (5 mg kg-1) significantly reduced levels of phospho-PKR in muscle down to that found in non-tumour-bearing mice, and effectively attenuated the depression of body weight, with increased muscle mass, and also inhibited tumour growth. There was an increase in protein synthesis in skeletal muscle, which paralleled a decrease in eukaryotic initiation factor 2α phosphorylation. Protein degradation rates in skeletal muscle were also significantly decreased, as was proteasome activity levels and expression. Myosin levels were increased up to values found in non-tumour-bearing animals. Proteasome expression correlated with a decreased nuclear accumulation of nuclear factor-κB (NF-κB). The PKR inhibitor also significantly inhibited tumour growth, although this appeared to be a separate event from the effect on muscle wasting. These results suggest that inhibition of the autophosphorylation of PKR may represent an appropriate target for the attenuation of muscle atrophy in cancer cachexia. © 2007 Cancer Research UK.

Breakage model development and application with CFD for predicting breakage of whey protein precipitate particles

Particle breakage due to fluid flow through various geometries can have a major influence on the performance of particle/fluid processes and on the product quality characteristics of particle/fluid products. In this study, whey protein precipitate dispersions were used as a case study to investigate the effect of flow intensity and exposure time on the breakage of these precipitate particles. Computational fluid dynamic (CFD) simulations were performed to evaluate the turbulent eddy dissipation rate (TED) and associated exposure time along various flow geometries. The focus of this work is on the predictive modelling of particle breakage in particle/fluid systems. A number of breakage models were developed to relate TED and exposure time to particle breakage. The suitability of these breakage models was evaluated for their ability to predict the experimentally determined breakage of the whey protein precipitate particles. A "power-law threshold" breakage model was found to provide a satisfactory capability for predicting the breakage of the whey protein precipitate particles. The whey protein precipitate dispersions were propelled through a number of different geometries such as bends, tees and elbows, and the model accurately predicted the mean particle size attained after flow through these geometries. © 2005 Elsevier Ltd. All rights reserved.

Tissue-specific selection of reference genes is required for expression studies in the mouse model of maternal protein undernutrition

Suboptimal maternal nutrition during gestation results in the establishment of long-term phenotypic changes and an increased disease risk in the offspring. To elucidate how such environmental sensitivity results in physiological outcomes, the molecular characterisation of these offspring has become the focus of many studies. However, the likely modification of key cellular processes such as metabolism in response to maternal undernutrition raises the question of whether the genes typically used as reference constants in gene expression studies are suitable controls. Using a mouse model of maternal protein undernutrition, we have investigated the stability of seven commonly used reference genes (18s, Hprt1, Pgk1, Ppib, Sdha, Tbp and Tuba1) in a variety of offspring tissues including liver, kidney, heart, retro-peritoneal and inter-scapular fat, extra-embryonic placenta and yolk sac, as well as in the preimplantation blastocyst and blastocyst-derived embryonic stem cells. We find that although the selected reference genes are all highly stable within this system, they show tissue, treatment and sex-specific variation. Furthermore, software-based selection approaches rank reference genes differently and do not always identify genes which differ between conditions. Therefore, we recommend that reference gene selection for gene expression studies should be thoroughly validated for each tissue of interest. © 2011 Elsevier Inc.

Protein interactions studied by SAXS:effect of ionic strength and protein concentration for BSA in aqueous solutions

We have studied a series of samples of bovine serum albumin (BSA) solutions with protein concentration, c, ranging from 2 to 500 mg/mL and ionic strength, I, from 0 to 2 M by small-angle X-ray scattering (SAXS). The scattering intensity distribution was compared to simulations using an oblate ellipsoid form factor with radii of 17 x 42 x 42 A, combined with either a screened Coulomb, repulsive structure factor, S-SC(q), or an attractive square-well structure factor, S-SW(q). At pH = 7, BSA is negatively charged. At low ionic strength, I <0.3 M, the total interaction exhibits a decrease of the repulsive interaction when compared to the salt-free solution, as the net surface charge is screened, and the data can be fitted by assuming an ellipsoid form factor and screened Coulomb interaction. At moderate ionic strength (0.3-0.5 M), the interaction is rather weak, and a hard-sphere structure factor has been used to simulate the data with a higher volume fraction. Upon further increase of the ionic strength (I >= 1.0 M), the overall interaction potential was dominated by an additional attractive potential, and the data could be successfully fitted by an ellipsoid form factor and a square-well potential model. The fit parameters, well depth and well width, indicate that the attractive potential caused by a high salt concentration is weak and long-ranged. Although the long-range, attractive potential dominated the protein interaction, no gelation or precipitation was observed in any of the samples. This is explained by the increase of a short-range, repulsive interaction between protein molecules by forming a hydration layer with increasing salt concentration. The competition between long-range, attractive and short-range, repulsive interactions accounted for the stability of concentrated BSA solution at high ionic strength.

A proteo-liposome system for the analysis of the intracellular interactome of membrane proteins using amyloid precursor protein as a model

Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.