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Biomedical subjects

M Goodall

Publications and source records attributed to M Goodall.

52 records · Page 3Linked to original sources
PubMed1969

Dopamine (3-hydroxytyramine) metabolism in parkinsonism.

Three patients with idiopathic parkinsonism and six normal subjects were infused over a 4 hr period with 104.6 muc of dopamine-2-(14)C (3,4-dihydroxyphenylethylamine, 3-hydroxytyramine),(1) the immediate precursor in the synthesis of the sympathetic neurohormone, noradrenaline (norepinephrine). Urine was collected during the infusion period, 0-2 hr, 2-4 hr, 4-8 hr, 8-24 hr, and thereafter for 4 additional days. Using a technique herein described, the various metabolic and biosynthetic products of dopamine, including noradrenaline and its metabolic products, were separated, identified, and their radioactivity measured. The metabolic pattern of dopamine in the normal subject was compared to that of the three parkinsonism patients. The results indicate that in idiopathic parkinsonism there is a decrease in the recovery of free radioactive noradrenaline in the urine following an infusion of dopamine-2-(14)C and a slight shift toward dopamine metabolism. The latter is reflected by an increase in the following metabolites of dopamine: 3,4-dihydroxyphenylacetic acid and the conjugates of 3-methoxy-4-hydroxyphenylacetic acid, 3,4-dihydroxyphenylacetic acid, 3-methoxy-4-hydroxyphenylethanol and dopamine.

Adult↗
PubMedDate not supplied

The influence of glycosylation on the thermal stability and effector function expression of human IgG1-Fc: properties of a series of truncated glycoforms.

Antibodies are multifunctional molecules that following the formation of antibody antigen complexes, may activate mechanisms to effect the clearance and destruction of the antigen (pathogen). The IgG molecule is comprised of three globular protein moieties (2Fab+Fc) linked through a flexible hinge region. While the Fabs bind antigens, the Fc triggers effector mechanisms through interactions with specific ligands, e.g. cellular receptors (FcgammaR), and the C1 component of complement. Glycosylation of IgG-Fc has been shown to be essential for efficient activation of FcgammaR and C1. We report the generation of a series of truncated glycoforms of IgG-Fc, and the analysis of the contribution of the residual oligosaccharide to IgG-Fc function and thermal stability. Differential scanning microcalorimetry has been used to compare the stabilities of the homogeneous glycoforms of IgG1-Fc. The results show that all truncated oligosaccharides confer a degree of functional activity, and thermodynamic stability to the IgG1-Fc, in comparison with deglycosylated IgG1-Fc. The same truncated glycoforms of an intact IgG1 anti-MHC Class II antibody are shown to exhibit differential functional activity for FcgammaRI and C1 ligands, relative to deglycosylated IgG1. The minimal glycoform investigated had a trisaccharide attached to each heavy chain and can be expected to influence protein structure primarily in the proximity of the N-terminal region of the C(H)2 domain, implicated as a binding site for multiple effector ligands. These data provide a thermodynamic rationale for the modulation of antibody effector functions by different glycoforms.

Calorimetry, Differential Scanning↗
PubMedDate not supplied

Automated testing of arrhythmia monitors using annotated databases.

Arrhythmia-algorithm performance is typically tested using the AHA and MIT/BIH databases. The tools for this test are simulation software programs. While these simulations provide rapid results, they neglect hardware and software effects in the monitor. To provide a more accurate measure of performance in the actual monitor, a system has been developed for automated arrhythmia testing. The testing system incorporates an IBM-compatible personal computer, a digital-to-analog converter, an RS232 board, a patient-simulator interface to the monitor, and a multi-tasking software package for data conversion and communication with the monitor. This system "plays" patient data files into the monitor and saves beat classifications in detection files. Tests were performed using the MIT/BIH and AHA databases. Statistics were generated by comparing the detection files with the annotation files. These statistics were marginally different from those that resulted from the simulation. Differences were then examined. As expected, the differences were related to monitor hardware effects.

Algorithms↗