Specific effects of 9- and 13- hydroxyoctadecadienoic acids (9- and 13- hodes) on human monocyte activation and macrophage differentiation

In diabetes, activation of monocytes, macrophage differentiation in arterial walls, and foam cell formation are increased contributing to macrovascular complications. Mechanisms regulating these processes are incompletely understood. HODEs are oxidised linoleic acid (LA) derivatives produced non-enzymatically from LDL (oxLDL) or by enzyme 15- lipoxygenase. 9-HODE, (n-6) is pro-inflammatory and may act through the GPR132 receptor, while 13-HODE, (n-7), may have protective effects similar to palmitoleate (also n-7). We studied effects of long chain fatty acids (LCFA) HODEs, LA and α-linolenic acid (C18, n-3, ALA) on differentiation and gene expression in THP-1 cells. Monocytes were fully differentiated into macrophages with 100nM phorbol myristate acetate (PMA), while 1 nM PMA synergized with 30 µM LCFAs increased expression of activation marker CD11b, macrophage morphology and lipid accumulation (oil red-O). Monocyte cell number was decreased by HODEs (p < 0.001) but not LA or ALA. Decreased cell viability was confirmed, and shown to be due to apoptosis (caspase 3/7 activation) rather than cytotoxicity. Monocyte activation (PMA 100 nM or PMA 1nM + 30µM HODEs) markedly increased expression of lipogenic genes FABP4 and PPARγ. Genes involved in reverse cholesterol transport (ABCA1 and SCRB) were activated by HODEs. These effects were not seen to be induced by ALA and LA. Stearoyl CoA desaturase, increased in insulin resistance, was decreased in monocytes by 13-HODE, but increased during activation and in macrophages by 9-HODE. 9-HODE specifically increased foam cells (lipid droplets) in differentiated macrophage cultures. Possible mediators of fatty acid effects include long-chain fatty acid receptors (GPR120 and GPR132) and PPARγ. GPR120 was predominantly expressed in monocytes and GPR132 in macrophages (PCR and immuno-histochemistry) with 9-HODE increasing GPR132 expression. A decrease in expression of GPR120 and an increase in GPR132 was observed when treated with HODEs synergized with 1nM PMA. 9- and 13-HODE have specific effects on monocyte activation, macrophage differentiation, lipid transport and signaling genes compared to LA and ALA. Ongoing work with receptor activators/inhibitors and gene silencing will clarify which signaling pathways are involved in the actions of long-chain fatty acid mediators

The Use of Artificial Neural Networks to Predict Osteoporosis

Osteoporosis arises when the bone lose sufficient mineral to allow fractures to develop after only minimal trauma. It is an extremely common condition in post-menopausal women and is becoming more common because of the increasing number of elderly women in the population. The most devastating effects of osteoporosis arise when the patient fractures either the hip or the vertebrae. These conditions are painful and disabling and are frequently the precipitating factor for an elderly person having to give up an independent existence. The cost of treating the results of osteoporosis fractures is immense. We now have accurate and widely applicable methods for measuring the bone density and thus identifying patients at risk. However, the necessary scanners are not widely available and it is not thought to be profitable to screen the entire population at risk with bone scanners.......

Integrating STEM: An Interdisciplinary Approach to PreK-12 Education

STEM education employs an interdisciplinary pedagogical approach that merges the subjects of science, technology, engineering, and mathematics into traditional disciplines covered across all levels within primary and secondary school curricula. STEM topics span the United Nation’s Sustainable Development Goals (SDGs) and naturally weave STEM disciplines throughout, focusing on the importance of developing a global STEM-literate workforce capable of responding to the worldwide challenges presented today and into the future. STEM-focused frameworks provide students with the knowledge and skills they need to be successful in the twenty first century and beyond, preparing them for the rapidly changing technological and scientific landscapes. This chapter explores STEM as a meta-discipline, documenting the origins and emergence of STEM education in the United States, provides definitions of STEM literacy and includes primary and secondary implementation models

The Intentional Use of Service Recovery Strategies to Influence Consumer Emotion, Cognition and Behaviour

Service recovery strategies have been identified as a critical factor in the success of. service organizations. This study develops a conceptual frame work to investigate how specific service recovery strategies influence the emotional, cognitive and negative behavioural responses of . consumers., as well as how emotion and cognition influence negative behavior. Understanding the impact of specific service recovery strategies will allow service providers' to more deliberately and intentionally engage in strategies that result in positive organizational outcomes. This study was conducted using a 2 x 2 between-subjects quasi-experimental design. The results suggest that service recovery has a significant impact on emotion, cognition and negative behavior. Similarly, satisfaction, negative emotion and positive emotion all influence negative behavior but distributive justice has no effect

Data visualisations : newsroom trends and everyday engagements

This chapter looks at both the production of data visualizations (henceforth “dataviz”) in newsrooms and audiences’ everyday engagements with dataviz, drawing on two separate research projects. The first is Seeing Data, which explored how people make sense of data visualizations, and the second is INDVIL, which explored dataviz as a semiotic, aesthetic and discursive resource in society. The chapter starts by summarizing the main findings of an INDVIL sub-project focusing on dataviz in the news, in which we found that dataviz are perceived in diverse ways and deployed for diverse purposes. It then summarizes our main findings from Seeing Data, where we also found great diversity, this time in how audiences make sense of dataviz. This diversity is important for the future work of both dataviz researchers and practitioners

Prediction of Severe Complications and Mortality in Patients Admitted to a Coronary Care Unit

The aim of this study was to design a statistical model which will predict death or life-threatening complications in patients admitted to Coronary Care Unit using data which is available at the time of presentation. The study included 3721 consecutive admissions over a period four year period. Predictive models were developed using logistic regression analysis (with data from 1000 patients) and their performance was assessed using receiver operating characteristic (ROC) curve analysis. The most useful model included nine data items and was tested on data from 2721 patients. These could be divided into four groups according to their calculated probability of developing a serious complication. The lowest risk group had a mortality of 0.05%, compared with 3.5%, 6.4% and 18.1% respectively in the higher risk groups (p1000 U/1) in the four groups was 14.1%, 21.2%, 46.9% and 51.5% respectively (p<0.001). The overall complication rates were 16.9%, 35.4%, 75.4% and 71.8% respectively (p<0.001)

A Two-Dimensional Model with Chiral Condensates and Cooper Pairs Having QCD-like Phase Structure

We describe how a generalization of the original Gross-Neveu model from U(N) to O(N) flavor symmetry leads to the appearance of a pairing condensate at high density, in agreement with the conjectured phenomenon of color superconductivity in $(3+1)$-dimensional QCD. Moreover, the model displays a rich phase structure which closely resembles the one expected in two-flavor QCD.Comment: 11 pages, 1 fugure, Presented at TMU-Yale Symposium on Dynamics of Gauge Fields: An External Activity of APCTP, Tokyo, Japan, 13-15 Dec 199

Open tubular liquid-chromatography and the analysis of single neurons

Liquid chromatography in open tubular columns (OTLC) offers a means of achieving separations of high resolving power within analysis times of minutes to hours. A theory which predicts the optimal dimensions for an open tubular column for a given set of analytical conditions has been developed [1]. This theory predicts that for a wide range of possible inlet pressures and analysis times the most efficient columns will result when the column inner diameter is between 1.5 and 3 μm. A column of 2 μm diameter and 2 meter length should be capable of producing a million theoretical plates for an analyte with a capacity factor of 10 (strongly retained) and a retention time of 100 minutes

Quantum spin systems at positive temperature

We develop a novel approach to phase transitions in quantum spin models based on a relation to their classical counterparts. Explicitly, we show that whenever chessboard estimates can be used to prove a phase transition in the classical model, the corresponding quantum model will have a similar phase transition, provided the inverse temperature $\beta$ and the magnitude of the quantum spins \CalS satisfy \beta\ll\sqrt\CalS. From the quantum system we require that it is reflection positive and that it has a meaningful classical limit; the core technical estimate may be described as an extension of the Berezin-Lieb inequalities down to the level of matrix elements. The general theory is applied to prove phase transitions in various quantum spin systems with \CalS\gg1. The most notable examples are the quantum orbital-compass model on $\Z^2$ and the quantum 120-degree model on $\Z^3$ which are shown to exhibit symmetry breaking at low-temperatures despite the infinite degeneracy of their (classical) ground state.Comment: 47 pages, version to appear in CMP (style files included

Optimal designs for rational function regression

We consider optimal non-sequential designs for a large class of (linear and nonlinear) regression models involving polynomials and rational functions with heteroscedastic noise also given by a polynomial or rational weight function. The proposed method treats D-, E-, A-, and $\Phi_p$-optimal designs in a unified manner, and generates a polynomial whose zeros are the support points of the optimal approximate design, generalizing a number of previously known results of the same flavor. The method is based on a mathematical optimization model that can incorporate various criteria of optimality and can be solved efficiently by well established numerical optimization methods. In contrast to previous optimization-based methods proposed for similar design problems, it also has theoretical guarantee of its algorithmic efficiency; in fact, the running times of all numerical examples considered in the paper are negligible. The stability of the method is demonstrated in an example involving high degree polynomials. After discussing linear models, applications for finding locally optimal designs for nonlinear regression models involving rational functions are presented, then extensions to robust regression designs, and trigonometric regression are shown. As a corollary, an upper bound on the size of the support set of the minimally-supported optimal designs is also found. The method is of considerable practical importance, with the potential for instance to impact design software development. Further study of the optimality conditions of the main optimization model might also yield new theoretical insights.Comment: 25 pages. Previous version updated with more details in the theory and additional example