Illness Self-Schema in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a relatively rare autoimmune disease with no known aetiology or cure. In addition to numerous physical symptoms, those living with SLE have also been shown to experience significant emotional and psychosocial difficulties. There has been little psychological research into SLE despite the rapidly increasing interest in health psychology and quality of life issues over the last two decades. One such issue that has commanded particular attention is that of cognitive bias in individuals with chronic pain and/or chronic illness. Cognitive bias toward illness-related information is theorised to indicate the presence of an illness self-schema, and is a valuable tool of investigation as it permits access to a level of cognitive structure that is inaccessible via self-report instruments. The primary focus of the present study is to investigate recall bias for pain- and illness-related words in SLE patients. This bias is explored relative to the recall of neutral words and depression-related words, and also relative to the responses of rheumatoid arthritis (RA) patients and healthy controls. Two hypotheses are proposed: firstly, that bias is related to disease activity; and secondly, that bias is related to the combination of illness and depression. The findings provide support for the second hypothesis, with the additional caveat that the nature of the pain/illness stimuli used is important in determining the presence of cognitive bias. No recall bias for illness-related words as a whole was found in any of the groups, nor was there evidence of a recall bias in the SLE and RA patients when they were divided according to depression status. However, when the illness words were examined separately according to �sensory pain� and �disability-related� words, a clear bias for disability words was found in the depressed patient group. It is concluded that there is a relationship between depression in chronically ill individuals, and the way in which such individuals process disability-related words. In accordance with the schema-enmeshment model (Pincus & Morley, 2001), it is suggested that both a pain-schema and an illness-schema exist, and it is when these two schemas become enmeshed with the self-schema that depression occurs in chronic pain/chronically ill patients. The cognitive bias assessment paradigm adopted in this study-one that is typically used in similar investigations-is lengthy, requires sophisticated equipment and can be difficult to interpret on an individual level. The present study investigates the relationship between cognitive biases in SLE patients and a recently-developed task, PRISM, which appears to symbolise the enmeshment of illness-, pain- and self-schemas. Analyses confirmed that recall of negative illness words was the only independent predictor of PRISM scores. This suggests that PRISM, a quick and easy task to administer, may have considerable usefulness as a clinical tool to assess information relevant to the enmeshment of illness- and self-schema. A greater understanding of schema and the processing styles of chronically ill patients will allow for more effective psychological treatment such that quality of life can be improved

Offspring outcomes after prenatal interventions for common mental disorders:a meta-analysis

Background: It is presumed that pharmacological and non-pharmacological treatment of prenatal common mental disorders can mitigate associated adverse effects in offspring, yet strong evidence for the prophylactic benefits of treatment is lacking. We therefore examined the effect of prenatal treatments for common mental disorders on offspring outcomes. Methods: For this meta-analysis, articles published up to August 31, 2017, were obtained from PubMed, PsycInfo, Embase, and Cochrane databases. Included studies needed to be randomized controlled trials (RCTs) on the effect of treatment of prenatal common mental disorders comparing an intervention to a control condition, including offspring outcome(s). Random effects models were used to calculate Hedges' g in the program Comprehensive Meta-Analysi

Ovalbumin-Induced Epithelial Activation Directs Monocyte-Derived Dendritic Cells to Instruct Type 2 Inflammation in T Cells Which Is Differentially Modulated by 2'-Fucosyllactose and 3-Fucosyllactose

Allergic sensitization starts with epithelial cell activation driving dendritic cells (DCs) to instruct T helper 2 (Th2) cell polarization. Food allergens trigger intestinal epithelial cell (IEC) activation. Human milk oligosaccharides may temper the allergic phenotype by shaping mucosal immune responses.We investigated in vitro mucosal immune development after allergen exposure by combining ovalbumin (OVA)-preexposed IEC with monocyte-derived DCs (OVA-IEC-DCs) and subsequent coculture of OVA-IEC-DCs with Th cells. IECs were additionally preincubated with 2'FL or 3FL.OVA activation increased IEC cytokine secretion. OVA-IEC-DCs instructed both IL13 (p < 0.05) and IFNγ (p < 0.05) secretion from Th cells. 2'FL and 3FL permitted OVA-induced epithelial activation, but 2'FL-OVA-IEC-DCs boosted inflammatory and regulatory T-cell development. 3FL-OVA-IEC lowered IL12p70 and IL23 in DCs and suppressed IL13 (p < 0.005) in T cells, while enhancing IL17 (p < 0.001) and IL10 (p < 0.005).These results show that OVA drives Th2- and Th1-type immune responses via activation of IECs in this model. 2'FL and 3FL differentially affect OVA-IEC-driven immune effects. 2'FL boosted overall T-cell OVA-IEC immunity via DC enhancing inflammatory and regulatory responses. 3FL-OVA-IEC-DCs silenced IL13, shifting the balance towards IL17 and IL10.This model demonstrates the contribution of IEC to OVA Th2-type immunity. 2'FL and 3FL modulate the OVA-induced activation in this novel model to study allergic sensitization

Array Formatting of the Heat-Transfer Method (HTM) for the Detection of Small Organic Molecules by Molecularly Imprinted Polymers

In this work we present the first steps towards a molecularly imprinted polymer (MIP)-based biomimetic sensor array for the detection of small organic molecules via the heat-transfer method (HTM). HTM relies on the change in thermal resistance upon binding of the target molecule to the MIP-type receptor. A flow-through sensor cell was developed, which is segmented into four quadrants with a volume of 2.5 μL each, allowing four measurements to be done simultaneously on a single substrate. Verification measurements were conducted, in which all quadrants received a uniform treatment and all four channels exhibited a similar response. Subsequently, measurements were performed in quadrants, which were functionalized with different MIP particles. Each of these quadrants was exposed to the same buffer solution, spiked with different molecules, according to the MIP under analysis. With the flow cell design we could discriminate between similar small organic molecules and observed no significant cross-selectivity. Therefore, the MIP array sensor platform with HTM as a readout technique, has the potential to become a low-cost analysis tool for bioanalytical applications

Dipstick sensor based on molecularly imprinted polymer-coated screen-printed electrodes for the single-shot detection of glucose in urine samples—from fundamental study toward point-of-care application

Glucose biosensors play an extremely important role in health care systems worldwide. Therefore, the field continues to attract significant attention leading to the development of innovative technologies. Due to their characteristics, Molecularly Imprinted Polymers (MIPs) represent a promising alternative to commercial enzymatic sensors. In this work, a low-cost, flexible MIP-based platform for glucose sensing by integrating MIP particles directly into screen-printed electrodes (SPEs) is realized. The sensor design allows the detection of glucose via two different transducer principles, the so-called “heat-transfer method” (HTM) and electrochemical impedance spectroscopy (EIS). The sensitivity and selectivity of the sensor are demonstrated by comparing the responses obtained toward three different saccharides. Furthermore, the application potential of the MIP-SPE sensor is demonstrated by analyzing the response in urine samples, showing a linear range of 14.38–330 µm with HTM and 1.37–330 µm with EIS. To bring the sensor closer to a real life application, a handheld dipstick sensor is developed, allowing the single-shot detection of glucose in urine using EIS. This study illustrates that the simplicity of the dipstick readout coupled with the straightforward manufacturing process opens up the possibility for mass production, making this platform a very attractive alternative to commercial glucose sensors

Label-Free Detection of Escherichia coli Based on Thermal Transport through Surface Imprinted Polymers

This work focuses on the development of a label-free biomimetic sensor for the specific and selective detection of bacteria. The platform relies on the rebinding of bacteria to synthetic cell receptors, made by surface imprinting of polyurethane-coated aluminum chips. The heat-transfer resistance (Rth) of these so-called surface imprinted polymers (SIPs) was analyzed in time using the heat-transfer method (HTM). Rebinding of target bacteria to the synthetic receptor led to a measurable increase in thermal resistance at the solid–liquid interface. Escherichia coli and Staphylococcus aureus were used as model organisms for several proof-of-principle experiments, demonstrating the potential of the proposed platform for point-of-care bacterial testing. The results of these experiments indicate that the sensor is able to selectively detect bacterial rebinding to the SIP surface, distinguishing between dead and living E. coli cells on one hand and between Gram-positive and Gram-negative bacteria on the other hand (E. coli and S. aureus). In addition, the sensor was capable of quantifying the number of bacteria in a given sample, enabling detection at relatively low concentrations (104 CFU mL–1 range). As a first proof-of-application, the sensor was exposed to a mixed bacterial solution containing only a small amount (1%) of the target bacteria. The sample was able to detect this trace amount by using a simple gradual enrichment strategy

Do Bankart lesions heal better in shoulders immobilized in external rotation?: A randomized single-blind study of 55 patients examined with MRI

Background and purpose Immobilization in external rotation (ER) for shoulder dislocation has been reported to improve the coaptation of Bankart lesions to the glenoid. We compared the position of the labrum in patients treated with immobilization in ER or internal rotation (IR). A secondary aim was to evaluate the rate of Bankart lesions

A Novel Biomimetic Tool for Assessing Vitamin K Status Based on Molecularly Imprinted Polymers

Vitamin K was originally discovered as a cofactor required to activate clotting factors and has recently been shown to play a key role in the regulation of soft tissue calcification. This property of vitamin K has led to an increased interest in novel methods for accurate vitamin K detection. Molecularly Imprinted Polymers (MIPs) could offer a solution, as they have been used as synthetic receptors in a large variety of biomimetic sensors for the detection of similar molecules over the past few decades, because of their robust nature and remarkable selectivity. In this article, the authors introduce a novel imprinting approach to create a MIP that is able to selectively rebind vitamin K 1. As the native structure of the vitamin does not allow for imprinting, an alternative imprinting strategy was developed, using the synthetic compound menadione (vitamin K 3) as a template. Target rebinding was analyzed by means of UV-visible (UV-VIS) spectroscopy and two custom-made thermal readout techniques. This analysis reveals that the MIP-based sensor reacts to an increasing concentration of both menadione and vitamin K 1. The Limit of Detection (LoD) for both compounds was established at 700 nM for the Heat Transfer Method (HTM), while the optimized readout approach, Thermal Wave Transport Analysis (TWTA), displayed an increased sensitivity with a LoD of 200 nM. The sensor seems to react to a lesser extent to Vitamin E, the analogue under study. To further demonstrate its potential application in biochemical research, the sensor was used to measure the absorption of vitamin K in blood serum after taking vitamin K supplements. By employing a gradual enrichment strategy, the sensor was able to detect the difference between baseline and peak absorption samples and was able to quantify the vitamin K concentration in good agreement with a validation experiment using High-Performance Liquid Chromatography (HPLC). In this way, the authors provide a first proof of principle for a low-cost, straightforward, and label-free vitamin K sensor

Biomimetic Bacterial Identification Platform Based on Thermal Wave Transport Analysis (TWTA) through Surface-Imprinted Polymers

This paper introduces a novel bacterial identification assay based on thermal wave analysis through surfaceimprinted polymers (SIPs). Aluminum chips are coated with SIPs, serving as synthetic cell receptors that have been combined previously with the heat-transfer method (HTM) for the selective detection of bacteria. In this work, the concept of bacterial identification is extended toward the detection of nine different bacterial species. In addition, a novel sensing approach, thermal wave transport analysis (TWTA), is introduced, which analyzes the propagation of a thermal wave through a functional interface. The results presented here demonstrate that bacterial rebinding to the SIP layer resulted in a measurable phase shift in the propagated wave, which is most pronounced at a frequency of 0.03 Hz. In this way, the sensor is able to selectively distinguish between the different bacterial species used in this study. Furthermore, a dose−response curve was constructed to determine a limit of detection of 1 × 104 CFU mL−1 , indicating that TWTA is advantageous over HTM in terms of sensitivity and response time. Additionally, the limit of selectivity of the sensor was tested in a mixed bacterial solution, containing the target species in the presence of a 99-fold excess of competitor species. Finally, a first application for the sensor in terms of infection diagnosis is presented, revealing that the platform is able to detect bacteria in clinically relevant concentrations as low as 3 × 104 CFU mL−1 in spiked urine samples