The adoption of Application Specific Integrated Circuit (ASIC) technology by the UK manufacturing base

Since the late 1970s, families of microelectronic technologies that could bring the advantages of high levels of electronic integration have been available at reasonable prices and manageable risk to all sectors of UK industry. However, the uptake of these technologies has been painfully slow, particularly by the small and medium enterprises (SMEs) that make up most of the companies currently operating in the UK. It is the aim of the research described here to assess how slow the uptake has been, the reasons for it, and possible solutions to the problem. The problem is investigated with reference to SMEs. In order to reach conclusions it has been necessary to:- • Define Application Specific Integrated Circuit (ASIC) technology and review its history • Review that nature of the UK SME base and identify why they should use ASICs • Review the UK, European and World ASIC markets • Analyse the nature of the UK ASIC design and supply industry • Ascertain the reasons for non-adoption and assess their validity • Relate the findings of this research to appropriate business, organisational and system models • Review past and existing technology-transfer programmes operating in the area of ASIC adoption at a UK, European and world level • Compare the adoption of ASIC technology with the adoption of similar, wide-ranging, new technologies The study concludes that the technology is unique in the wide range of industries to which it can be applied, and that although some advances in adoption have been made, there remains a significant number of hurdles to adoption which can best be addressed by government intervention and supporting activity from supply-companies, trade associations, user-groups and professional and educational institutions. Only once adoption has reached a 'critical mass' can it be assumed that a self-sustaining market will result

Identification of (poly)phenol treatments that modulate the release of pro-inflammatory cytokines by human lymphocytes

Diets rich in fruits and vegetables (FV), which contain (poly)phenols, protect against age-related inflammation and chronic diseases. T-lymphocytes contribute to systemic cytokine production and are modulated by FV intake. Little is known about the relative potency of different (poly)phenols in modulating cytokine release by lymphocytes. We compared thirty-one (poly)phenols and six (poly)phenol mixtures for effects on pro-inflammatory cytokine release by Jurkat T-lymphocytes. Test compounds were incubated with Jurkat cells for 48 h at 1 and 30 µm, with or without phorbol ester treatment at 24 h to induce cytokine release. Three test compounds that reduced cytokine release were further incubated with primary lymphocytes at 0·2 and 1 µm for 24 h, with lipopolysaccharide added at 5 h. Cytokine release was measured, and generation of H2O2 by test compounds was determined to assess any potential correlations with cytokine release. A number of (poly)phenols significantly altered cytokine release from Jurkat cells (P<0·05), but H2O2 generation did not correlate with cytokine release. Resveratrol, isorhamnetin, curcumin, vanillic acid and specific (poly)phenol mixtures reduced pro-inflammatory cytokine release from T-lymphocytes, and there was evidence for interaction between (poly)phenols to further modulate cytokine release. The release of interferon-γ induced protein 10 by primary lymphocytes was significantly reduced following treatment with 1 µm isorhamnetin (P<0·05). These results suggest that (poly)phenols derived from onions, turmeric, red grapes, green tea and açai berries may help reduce the release of pro-inflammatory mediators in people at risk of chronic inflammation

Plasma membrane expression of GnRH receptors: regulation by antagonists in breast, prostate, and gonadotrope cell lines

In heterologous expression systems, human GnRH receptors (hGnRHRs) are poorly expressed at the cell surface and this may reflect inefficient exit from the endoplasmic reticulum. Here, we have defined the proportion of GnRHRs at the cell surface using a novel assay based on adenoviral transduction with epitope-tagged GnRHRs followed by staining and semi-automated imaging. We find that in MCF7 (breast cancer) cells, the proportional cell surface expression (PCSE) of hGnRHRs is remarkably low (<1%), when compared with Xenopus laevis (X) GnRHRs (∼40%). This distinction is retained at comparable whole cell expression levels, and the hGnRHR PCSE is increased by addition of the XGnRHR C-tail (h.XGnRHR) or by a membrane-permeant pharmacological chaperone (IN3). The IN3 effect is concentration- and time-dependent and IN3 also enhances the hGnRHR-mediated (but not h.XGnRHR- or mouse GnRHR-mediated) stimulation of [3H]inositol phosphate accumulation and the hGnRHR-mediated reduction in cell number. We also find that the PCSE for hGnRHRs and h.XGnRHRs is low and is greatly increased by IN3 in two hormone-dependent cancer lines, but is higher and less sensitive to IN3 in a gonadotrope line. Finally, we show that the effect of IN3 on hGnRHR PCSE is not mimicked or blocked by two peptide antagonists although they do increase the PCSE for h.XGnRHRs, revealing that an antagonist-occupied cell surface GnRHR conformation can differ from that of the unoccupied receptor. The low PCSE of hGnRHRs and this novel peptide antagonist effect may be important for understanding GnRHR function in extrapituitary sites

Using automated imaging to interrogate gonadotrophin-releasing hormone receptor trafficking and function

Gonadotrophin-releasing hormone (GnRH) acts via seven transmembrane receptors on gonadotrophs to stimulate gonadotrophin synthesis and secretion, and thereby mediates central control of reproduction. Type I mammalian GnRHR are unique, in that they lack C-terminal tails. This is thought to underlie their resistance to rapid homologous desensitisation as well as their slow rate of internalisation and inability to provoke G-protein-independent (arrestin-mediated) signalling. More recently it has been discovered that the vast majority of human GnRHR are actually intracellular, in spite of the fact that they are activated at the cell surface by a membrane impermeant peptide hormone. This apparently reflects inefficient exit from the endoplasmic reticulum and again, the absence of the C-tail likely contributes to their intracellular localisation. This review is intended to cover some of these novel aspects of GnRHR biology, focusing on ways that we have used automated fluorescence microscopy (high content imaging) to explore GnRHR localisation and trafficking as well as spatial and temporal aspects of GnRH signalling via the Ca(2+)/calmodulin/calcineurin/NFAT and Raf/MEK/ERK pathways

Evaluation of daily walking activity and gait profiles: a novel application of a time series analysis framework

Wearable technology allows an in-depth analysis of gait behaviour in free-living environments. This investigation aimed to use Alzheimer's disease as an example to apply the time series analysis technique of Statistical Parametric Mapping (SPM) to create daily gait profiles and test if they differed from cognitively intact controls. A framework of macro (habitual walking behaviours) and micro characteristics (spatiotemporal gait variables) characteristics were calculated on an hourly basis. SPM showed that select micro gait characteristics differed from controls at specific hours of the day. Therefore, the application of SPM may provide a more in-depth reflection of activity and gait time-dependent fluctuations than commonly used whole day values. Considering macro and micro gait hour-by- hour may have applications towards disease management, personalized care, monitoring medication and targeted interventions for people with a range of neurodegenerative diseases

The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control

Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions—including Parkinson’s disease, ataxia, and dementia— we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel ‘big data’ approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction

Information Transfer in Gonadotropin-Releasing Hormone (GnRH) Signaling:Extracellular Signal-Regulated Kinase (ERK)-Mediated Feedback Loops Control Hormone Sensing

Cell signaling pathways are noisy communication channels, and statistical measures derived from information theory can be used to quantify the information they transfer. Here we use single cell signaling measures to calculate mutual information as a measure of information transfer via gonadotropin-releasing hormone (GnRH) receptors (GnRHR) to extracellular signal-regulated kinase (ERK) or nuclear factor of activated T-cells (NFAT). This revealed mutual information values <1 bit, implying that individual GnRH-responsive cells cannot unambiguously differentiate even two equally probable input concentrations. Addressing possible mechanisms for mitigation of information loss, we focused on the ERK pathway and developed a stochastic activation model incorporating negative feedback and constitutive activity. Model simulations revealed interplay between fast (min) and slow (min-h) negative feedback loops with maximal information transfer at intermediate feedback levels. Consistent with this, experiments revealed that reducing negative feedback (by expressing catalytically inactive ERK2) and increasing negative feedback (by Egr1-driven expression of dual-specificity phosphatase 5 (DUSP5)) both reduced information transfer from GnRHR to ERK. It was also reduced by blocking protein synthesis (to prevent GnRH from increasing DUSP expression) but did not differ for different GnRHRs that do or do not undergo rapid homologous desensitization. Thus, the first statistical measures of information transfer via these receptors reveals that individual cells are unreliable sensors of GnRH concentration and that this reliability is maximal at intermediate levels of ERK-mediated negative feedback but is not influenced by receptor desensitization

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

Objective: We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk. Methods: We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors. Results: We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the previous AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio [OR] per SD = 1.40, p = 1.45 × 10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per SD = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1). Conclusions: Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF

Non-Hydrolytic β-Lactam Antibiotic Fragmentation by l,d-Transpeptidases and Serine β-Lactamase Cysteine Variants

Enzymes often use nucleophilic serine, threonine, and cysteine residues to achieve the same type of reaction; the underlying reasons for this are not understood. While bacterial d,d‐transpeptidases (penicillin‐binding proteins) employ a nucleophilic serine, l,d‐transpeptidases use a nucleophilic cysteine. The covalent complexes formed by l,d‐transpeptidases with some β‐lactam antibiotics undergo non‐hydrolytic fragmentation. This is not usually observed for penicillin‐binding proteins, or for the related serine β‐lactamases. Replacement of the nucleophilic serine of serine β‐lactamases with cysteine yields enzymes which fragment β‐lactams via a similar mechanism as the l,d‐transpeptidases, implying the different reaction outcomes are principally due to the formation of thioester versus ester intermediates. The results highlight fundamental differences in the reactivity of nucleophilic serine and cysteine enzymes, and imply new possibilities for the inhibition of nucleophilic enzymes