Citations

Abstract Motivation: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for 16O/18O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of 16O/18O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies. Contact: eckel@mayo.edu

Abstract Motivation: The need for normalization in microarray experiments has been well documented in the literature. Currently, many analysis methods treat normalization and analysis as a series of steps, with summarized data carried forward to the next step. Results: We present a unified algorithm which incorporates normalization and class comparison in one analysis using probe level perfect match and mismatch data. The algorithm is based on calibration models common to most biological assays, and the resulting chip-specific parameters have a natural interpretation. We show that the algorithm fits into the statistical generalized linear models framework, describe a practical fitting strategy and present results of the algorithm applied to an example dataset as well as based on metrics used in affycomp. The algorithm ranks amongst the top third of the affycomp competitors, performing best in measures of bias. Availability: R functions are available on request from the authors. Contact: oberg.ann@mayo.edu

The sex steroids, androgens and estrogens, are major regulators of bone metabolism. However, whether these hormones act on bone cells through direct or indirect mechanisms has remained unclear. A nuclear binding assay recently used to demonstrate estrogen receptors in bone [Eriksen, E.F., Colvard, D.S., Berg, N.J., Graham, M.L., Mann, K.G., Spelsberg, T.C. & Riggs, B.L. (1988) Science 241, 84-86] was used to identify specific nuclear binding of a tritiated synthetic androgen, [3H]R1881 (methyltrienolone), in 21 of 25 (84%) human osteoblast-like cell strains and a concentration of bound steroid receptors of 821 +/- 140 (mean +/- SEM) molecules per cell nucleus. Binding was saturable and steroid-specific. Androgen receptor gene expression in osteoblasts was confirmed by RNA blot analysis. Relative concentrations of androgen and estrogen receptors were compared by measuring specific nuclear estrogen binding. Nuclear binding of [3H]estradiol was observed in 27 of 30 (90%) cell strains; the concentration of bound estradiol receptor was 1537 +/- 221 molecules per cell nucleus. The concentrations of nuclear binding sites were similar in males and females for both [3H]R1881 and [3H]estradiol. We conclude that both androgens and estrogens act directly on human bone cells through their respective receptor-mediated mechanisms.

A cDNA library, prepared from poly(A)+ RNA isolated from quiescent AKR-2B cells 4 hr after stimulation with epidermal growth factor in the presence of cycloheximide, was screened to identify RNA transcripts whose abundance is specifically increased as a primary response to growth stimulation. Approximately 40% of the inducible clones detected by this procedure corresponded to either cytoskeletal beta- or gamma-actin genes. One nonactin clone, designated c99, was found to be derived from an 8.5-kilobase RNA whose abundance began to increase as early as 30 min after stimulation. DNA sequencing established the identity of this RNA as fibronectin. Several additional mitogens were then tested and found to efficiently induce fibronectin mRNA. These included fetal calf serum, platelet-derived growth factor, and transforming growth factor type beta. For at least one inducer, fetal calf serum, the increase in mRNA was preceded by an increase in fibronectin gene transcription. This increase was rapid, reaching maximal levels within 10 min, and was accompanied by near-coordinate increases in both c-fos and beta-actin transcription. These results indicate that fibronectin is a member of a class of "early-response" genes, typified by c-fos and including beta-actin, whose rapid expression may be important in mediating cellular responses to peptide growth factors.

Background— Atrioventricular (AV) nodal ablation for management of atrial fibrillation (AF) is irreversible and requires permanent pacemaker implantation. We hypothesized that as an alternative, implantation of autologous fibroblasts in the perinodal region would focally modify AV nodal conduction and that this modulation would be enhanced by pretreatment with transforming growth factor-β1 (TGF-β1), a stimulant of fibroblasts. Methods and Results— Skin biopsies were taken from 12 mongrel dogs, and derived fibroblasts were dissociated and grown in culture for 2 weeks. Multiple injections (0.25 mL) were made through an 8F NOGA catheter along the fast/slow AV nodal pathways as guided by an electroanatomic mapping system. Seven dogs received fibroblasts alone (1×10 6 cells/mL), 7 dogs received TGF-β1 (5 μg), 4 dogs received fibroblasts and TGF-β1 (1×10 6 cells/mL+5 μg), and 4 dogs received saline only. AV node function was assessed at baseline and after 4 weeks. Saline (80 mL) with assigned therapy (0.25 mL per injection) was injected into the peri-AV nodal region in each dog. At baseline, the AH interval (66±3 ms) and the average RR interval (331±17 ms) in pacing-induced AF were similar in each cohort. The increase in AH interval in normal sinus rhythm was longer after fibroblast (23±4 versus 5±5 ms; P =0.05) and fibroblast plus TGF-β1 (50±5 versus 5±5 ms; P <0.001) injections than with saline alone, with similar findings during high right atrium and distal coronary sinus pacing. The AH interval was not significantly increased after TGF-β1 injections. The AH interval was significantly longer after fibroblast plus TGF-β1 injections than with either therapy (TGF-β1 or fibroblasts) alone. The RR interval during AF was increased in dogs that received fibroblasts alone (110±36 versus −41±34 ms) and to a greater extent with the addition of TGF-β1 (294±108 versus −41±34 ms). No AV block was seen in any cohort at 4 weeks. Labeled fibroblasts that expressed vimentin were identified in all dogs that received cell injections at 4 weeks. Conclusions— AV nodal modification can be achieved with injected fibroblasts without the creation of AV block. The effect on AV node conduction is substantially enhanced by pretreatment of fibroblasts with TGF-β1. These data have therapeutic potential for the management of rapid ventricular rate during AF without pacemaker implantation.