Citations

Background . Clinicians often use validated risk models to guide treatment decisions for cardiovascular risk reduction. The most common risk models for predicting cardiovascular risk are the UKPDS, Framingham, and Archimedes models. In this article, the authors propose a model to optimize the selection of patients for statin therapy of hypercholesterolemia, for patients with type 2 diabetes, using each of the risk models. For each model, they evaluate the role of age, gender, and metabolic state on the optimal start time for statins. Method . Using clinical data from the Mayo Clinic electronic medical record, the authors construct a Markov decision process model with health states composed of cardiovascular events and metabolic factors such as total cholesterol and high-density lipoproteins. They use it to evaluate the optimal start time of statin treatment for different combinations of cardiovascular risk models and patient attributes. Results . The authors find that treatment decisions depend on the cardiovascular risk model used and the age, gender, and metabolic state of the patient. Using the UKPDS risk model to estimate the probability of coronary heart disease and stroke events, they find that all white male patients should eventually start statin therapy; however, using Framingham and Archimedes models in place of UKPDS, they find that for male patients at lower risk, it is never optimal to initiate statins. For white female patients, the authors also find some patients for whom it is never optimal to initiate statins. Assuming that age 40 is the earliest possible start time, the authors find that the earliest optimal start times for UKPDS, Framingham, and Archimedes are 50, 46, and 40, respectively, for women. For men, the earliest optimal start times are 40, 40, and 40, respectively. Conclusions . In addition to age, gender, and metabolic state, the choice of cardiovascular risk model influences the apparent optimal time for starting statins in patients with diabetes.

Object In a companion study, the authors describe the development of a new instrument named the Wireless Instantaneous Neurotransmitter Concentration System (WINCS), which couples digital telemetry with fast-scan cyclic voltammetry (FSCV) to measure extracellular concentrations of dopamine. In the present study, the authors describe the extended capability of the WINCS to use fixed potential amperometry (FPA) to measure extracellular concentrations of dopamine, as well as glutamate and adenosine. Compared with other electrochemical techniques such as FSCV or high-speed chronoamperometry, FPA offers superior temporal resolution and, in combination with enzyme-linked biosensors, the potential to monitor nonelectroactive analytes in real time. Methods The WINCS design incorporated a transimpedance amplifier with associated analog circuitry for FPA; a microprocessor; a Bluetooth transceiver; and a single, battery-powered, multilayer, printed circuit board. The WINCS was tested with 3 distinct recording electrodes: 1) a carbon-fiber microelectrode (CFM) to measure dopamine; 2) a glutamate oxidase enzyme–linked electrode to measure glutamate; and 3) a multiple enzyme–linked electrode (adenosine deaminase, nucleoside phosphorylase, and xanthine oxidase) to measure adenosine. Proof-of-principle analyses included noise assessments and in vitro and in vivo measurements that were compared with similar analyses by using a commercial hardwired electrochemical system (EA161 Picostat, eDAQ; Pty Ltd). In urethane-anesthetized rats, dopamine release was monitored in the striatum following deep brain stimulation (DBS) of ascending dopaminergic fibers in the medial forebrain bundle (MFB). In separate rat experiments, DBS-evoked adenosine release was monitored in the ventrolateral thalamus. To test the WINCS in an operating room setting resembling human neurosurgery, cortical glutamate release in response to motor cortex stimulation (MCS) was monitored using a large-mammal animal model, the pig. Results The WINCS, which is designed in compliance with FDA-recognized consensus standards for medical electrical device safety, successfully measured dopamine, glutamate, and adenosine, both in vitro and in vivo. The WINCS detected striatal dopamine release at the implanted CFM during DBS of the MFB. The DBS-evoked adenosine release in the rat thalamus and MCS-evoked glutamate release in the pig cortex were also successfully measured. Overall, in vitro and in vivo testing demonstrated signals comparable to a commercial hardwired electrochemical system for FPA. Conclusions By incorporating FPA, the chemical repertoire of WINCS-measurable neurotransmitters is expanded to include glutamate and other nonelectroactive species for which the evolving field of enzyme-linked biosensors exists. Because many neurotransmitters are not electrochemically active, FPA in combination with enzyme-linked microelectrodes represents a powerful intraoperative tool for rapid and selective neurochemical sampling in important anatomical targets during functional neurosurgery.

Object Emerging evidence supports the hypothesis that modulation of specific central neuronal systems contributes to the clinical efficacy of deep brain stimulation (DBS) and motor cortex stimulation (MCS). Real-time monitoring of the neurochemical output of targeted regions may therefore advance functional neurosurgery by, among other goals, providing a strategy for investigation of mechanisms, identification of new candidate neurotransmitters, and chemically guided placement of the stimulating electrode. The authors report the development of a device called the Wireless Instantaneous Neurotransmitter Concentration System (WINCS) for intraoperative neurochemical monitoring during functional neurosurgery. This device supports fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode (CFM) for real-time, spatially and chemically resolved neurotransmitter measurements in the brain. Methods The FSCV study consisted of a triangle wave scanned between −0.4 and 1 V at a rate of 300 V/second and applied at 10 Hz. All voltages were compared with an Ag/AgCl reference electrode. The CFM was constructed by aspirating a single carbon fiber (r = 2.5 μm) into a glass capillary and pulling the capillary to a microscopic tip by using a pipette puller. The exposed carbon fiber (that is, the sensing region) extended beyond the glass insulation by ~ 100 μm. The neurotransmitter dopamine was selected as the analyte for most trials. Proof-of-principle tests included in vitro flow injection and noise analysis, and in vivo measurements in urethane-anesthetized rats by monitoring dopamine release in the striatum following high-frequency electrical stimulation of the medial forebrain bundle. Direct comparisons were made to a conventional hardwired system. Results The WINCS, designed in compliance with FDA-recognized consensus standards for medical electrical device safety, consisted of 4 modules: 1) front-end analog circuit for FSCV (that is, current-to-voltage transducer); 2) Bluetooth transceiver; 3) microprocessor; and 4) direct-current battery. A Windows-XP laptop computer running custom software and equipped with a Universal Serial Bus–connected Bluetooth transceiver served as the base station. Computer software directed wireless data acquisition at 100 kilosamples/second and remote control of FSCV operation and adjustable waveform parameters. The WINCS provided reliable, high-fidelity measurements of dopamine and other neurochemicals such as serotonin, norepinephrine, and ascorbic acid by using FSCV at CFM and by flow injection analysis. In rats, the WINCS detected subsecond striatal dopamine release at the implanted sensor during high-frequency stimulation of ascending dopaminergic fibers. Overall, in vitro and in vivo testing demonstrated comparable signals to a conventional hardwired electrochemical system for FSCV. Importantly, the WINCS reduced susceptibility to electromagnetic noise typically found in an operating room setting. Conclusions Taken together, these results demonstrate that the WINCS is well suited for intraoperative neurochemical monitoring. It is anticipated that neurotransmitter measurements at an implanted chemical sensor will prove useful for advancing functional neurosurgery.

Abstract Previous studies have suggested that minor alleles for ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 may influence breast cancer risk, but the evidence is inconclusive due to their small sample size. These polymorphisms were genotyped in more than 30,000 breast cancer cases and 30,000 controls, primarily of European descent, from 30 studies in the Breast Cancer Association Consortium. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) as a measure of association. We found that the minor alleles for these polymorphisms were not related to invasive breast cancer risk overall in women of European descent: ECCR4 per-allele OR (95% CI) = 0.99 (0.97-1.02), minor allele frequency = 27.5%; TNF 1.00 (0.95-1.06), 5.0%; CASP10 1.02 (0.98-1.07), 6.5%; PGR 1.02 (0.99-1.06), 15.3%; and BID 0.98 (0.86-1.12), 1.7%. However, we observed significant between-study heterogeneity for associations with risk for single-nucleotide polymorphisms (SNP) in CASP10, PGR, and BID. Estimates were imprecise for women of Asian and African descent due to small numbers and lower minor allele frequencies (with the exception of BID SNP). The ORs for each copy of the minor allele were not significantly different by estrogen or progesterone receptor status, nor were any significant interactions found between the polymorphisms and age or family history of breast cancer. In conclusion, our data provide persuasive evidence against an overall association between invasive breast cancer risk and ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 genotypes among women of European descent. (Cancer Epidemiol Biomarkers Prev 2009;18(5):1610–6)

ABSTRACT A retrospective examination of quantitation standard growth curves associated with 1,000 unique clinical serum specimens tested by a laboratory-developed TaqMan hepatitis C virus analyte-specific reagent-based assay revealed anomalous growth curves associated with 0.40% (95% confidence interval, 0.11% to 1.00%) of these specimens.