Introduction We describe Alzheimer’s Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1–42), t-tau, and p-tau181 analytical performance, definition of Alzheimer’s disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. Methods Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1–42, t-tau, and p-tau181 data. Results CSFAD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. Discussion Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.
Everolimus displays a potent inhibitory effect on PTLD-derived cells in vitro and in vivo in a dose range leading to prevention of allograft rejection and may prove effective in both the prevention and treatment of PTLDs in transplant patients.
Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 ( n = 206), mixture modeling ( n = 216), and concordance with florbetapir F 18 imaging-based classification ( n = 75). Results A 1065-pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL). Discussion Based on three approaches, a 1100-pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling.
Measurement of unbound fractions of mycophenolic acid and its metabolites may prove useful in explaining the complicated pharmacokinetic and pharmacodynamic behavior of this drug as well as in therapeutic drug monitoring. We developed a reliable, accurate, and sensitive liquid chromatography-tandem mass spectrometric method for the simultaneous quantification of mycophenolic acid (MPA), MPA glucuronide (MPAG), and MPA acyl-glucuronide (AcMPAG), total or unbound, in plasma, urine, and tissue extract. This method uses a single internal standard, carboxy-butoxy ether of mycophenolic acid (MPAC), and involves a simple sample preparation step. Aliquots of plasma, urine, or dissolved tissue extract (100 microL) or plasma ultrafiltrate for free analytes (50 microL) are treated with acetonitrile/formic acid mixture (99.5/0.5 v/v) followed by centrifugation and dilution with water. The prepared samples are then injected onto an extraction column (Eclipse XDB-C18 12.5 x 4.1 mm; Agilent Technologies, Palo Alto, CA) and washed with mobile phase composed of acetonitrile/water/formic acid (10/89.5/0.5 v/v/v) at a flow rate of 2.8 mL/min. A switching valve is activated 1 minute after sample injection. The analytes are eluted onto the analytical column (Eclipse XDB-C18 150 x 4.1 mm; Agilent Technologies) with a gradient of 0.5% aqueous formic acid, methanol, acetonitrile, and water. We used a tandem mass spectrometer with electrospray ion source, in which the tandem mass spectroscopy transitions were (m/z): 338-->207 for MPA, 438-->303 for MPAC, and 514-->303 for MPAG and AcMPAG. The dynamic ranges (lower limit of quantitation and upper limit of quantitation) were as follows: 0.05 to 30 mg/L for total MPA and 1 to 300 microg/L for free MPA; 0.5 to 300 mg/L of total MPAG and 0.2 to 60 mg/L for free MPAG; and 0.025 to 15 mg/L of total AcMPAG and 1 to 60 microg/L for free AcMPAG. The precision at lower limit of quantitation was in the range of 8.0% to 11.9% for all three total analytes and 13.8 to 18.7% for the free analytes. Accuracy at lower limit of quantitation was in the range of 100% to 105% for total and 97% to 99% for free analytes. Between-day precision of quality control samples was 4.0% to 6.3% for human plasma spiked with total analytes and 4.5% to 14.4% for spiked plasma ultrafiltrate for free analytes. Mean absolute recovery ranged from 98.5% to 101.7% for MPA (both total and free), from 78.1% to 103.4% for MPAG and from 91.5% to 110.4% for AcMPAG. No significant ion suppression was found under these conditions for any of the analytes. Carryover effect was found to be at a maximum level of 0.02%. This method was successfully applied to analyze over 11,000 samples for total analytes, and over 8000 samples for free analytes in plasma, and has been in operation for nearly 3 years without loss of performance.
We studied a number of influences on theophylline binding to serum proteins using equilibrium dialysis (37 degrees), a modified Krebs-Ringer bicarbonate buffer (pH 7.4), and 8-14C-theophylline with unlabeled theophylline (30 microgram/ml) added to sera from healthy subjects. Theophylline protein binding rose by 18.6% as pH rose from 7.0 to 7.8 (percent theophylline bound = 28.2 +/- 4.3 at pH 7.0 and 46.8 +/- 4.9 at pH 7.8, n = 5). Average theophylline binding to the proteins at 37 degrees in serum samples from 10 normal adults was 39.3 +/- 3.44%, which is 89.9% lower than the average of 48.2 +/- 3.74% for the same samples at 26 degrees. Theophylline binding was 6.1% higher with 0.1 mole/l phosphate buffer, pH 7.4, than with a modified Krebs-Ringer bicarbonate buffer, pH 7.4. Of the 19 drugs and metabolites tested for competition with theophylline for binding sites on serum proteins, 10 induced decreases in binding ranging from 6.8% in the case of furosemide to 18.3% for sodium salicylate. The latter was the only drug that induced a decrease in theophylline binding at concentrations that would be achieved in the therapy of same patients (i.e., patients on long-term salicylate therapy). All the other drugs that decreased theophylline binding did so at much greater concentrations than their usual therapeutic levels. The mean +/- SD of theophylline bound in 51 fresh serum samples from healthy adults was 48.6 +/- 10.2%; the pH of these specimens varied from 7.6 to 8.7. After adjusting pH to 7.4, theophylline binding was lowered to 37.6 +/- 4.5% and intersubject variability decreased. We recommend that the pH of serum specimens be adjusted to 7.4, or to the original pH of the blood specimen if it differs significantly from 7.4 (i.e., in acidotic or alkalotic patients). The wide range of reported values for theophylline binding to serum proteins in normal and asthmatic adults at least partly results from differences in the conditions used for the separation of free from bound drug.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.