Hypersensitivity reactions to intravenous iron: guidance for risk minimization and management

Intravenous iron is widely used for the treatment of iron deficiency anemia when oral iron is inappropriate, ineffective or poorly tolerated. Acute hypersensitivity reactions during iron infusions are very rare but can be life-threatening. This paper reviews their frequency, pathogenesis and risk factors, and provides recommendations about their management and prevention. Complement activation-related pseudo-allergy triggered by iron nanoparticles is probably a more frequent pathogenetic mechanism in acute reactions to current formulations of intravenous iron than is an immunological IgE-mediated response. Major risk factors for hypersensitivity reactions include a previous reaction to an iron infusion, a fast iron infusion rate, multiple drug allergies, severe atopy, and possibly systemic inflammatory diseases. Early pregnancy is a contraindication to iron infusions, while old age and serious co-morbidity may worsen the impact of acute reactions if they occur. Management of iron infusions requires meticulous observation, and, in the event of an adverse reaction, prompt recognition and severity-related interventions by well-trained medical and nursing staff.     

Stochastic dynamic causal modeling of working memory connections in cocaine dependence

Although reduced working memory brain activation has been reported in several brain regions of cocaine‐dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging‐based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine‐dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level‐dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine‐dependent subjects had large differences compared with the control subjects in the strengths of prefrontal–striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical–striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between‐group DCM study using stochastic methodology. Hum Brain Mapp 35:760–778, 2014. © 2012 Wiley Periodicals, Inc.     

ZEUS (ZIF-based electrochemical ultrasensitive screening) device for isopentane analytics with focus on lung cancer diagnosis

Breath analytics is currently being explored for the development of point-of-care devices in non-invasive disease detection. It is based on the measurement of volatile organic compounds (VOCs) and gases that are produced by the body because of the metabolic pathways. The levels of these metabolites vary due to alteration in the endogenous oxidative stress-related metabolic pathways and can be correlated to understand the underlying disease condition. The levels of exhaled hydrocarbons in human breath can be used to design a rapid, easy to use method for lung cancer detection. This work outlines the development of an electrochemical sensing platform that can be used for the non-invasive diagnosis of lung cancer by monitoring isopentane levels in breath. This electrochemical sensor platform involves the use of [BMIM]BF₄@ZIF-8 for sensing the target analyte. This synthesized nanocomposite offers advantages for gas sensing applications as it possesses unique properties such as an electrochemically active Room Temperature Ionic Liquid (RTIL) and a crosslinking Metal Organic Framework (MOF) that provides increased surface area for gas absorption. This is the first report of a hydrocarbon-based sensor platform developed for lung cancer diagnosis. The developed sensor platform displays sensitivity and specificity for the detection of isopentane up to 600 parts-per-billion. We performed structural and morphological characterization of the synthesized nanocomposite using various analytical techniques such as PXRD, FESEM, FTIR, and DLS. We further analyzed the electrochemical activity of the synthesized nanocomposite using a standard glassy carbon electrode. The application of the nanocomposite for isopentane sensing was done using a commercially available carbon screen printed electrode. The results so obtained helped in strengthening our hypothesis and serve as a proof-of-concept for the development of a breathomics-enabled electrochemical strategy. We illustrated the specificity of the developed nanocomposite by cross-reactivity studies. We envision that the detection platform will allow sensitive and specific sensing of isopentane levels such that it can used for point of care applications in noninvasive and early diagnosis of lung cancer, thereby leading to its early treatment and decrease in mortality rate.

A novel synthesized [BMIM]BF₄@ZIF-8 nanocomposite for electrochemical sensing of isopentane as a biomarker for lung cancer diagnosis.     

Improving response rates and evaluating nonresponse bias in surveys: AMEE Guide No. 102

Robust response rates are essential for effective survey-based strategies. Researchers can improve survey validity by addressing both response rates and nonresponse bias. In this AMEE Guide, we explain response rate calculations and discuss methods for improving response rates to surveys as a whole (unit nonresponse) and to questions within a survey (item nonresponse). Finally, we introduce the concept of nonresponse bias and provide simple methods to measure it.