Citations

AbstractTwo simplified methods for quantitative lipoprotein analysis have been calibrated and compared with each other using analytic ultracentrifugation as a standard reference procedure. The first method was the Friedewald procedure and the second was an automated agarose gel electrophoresis system. Both procedures offer comparable quantitative lipoprotein analysis with potential for large scale screening purposes at low cost ($4.00–$5.00 per analysis). There were advantages and limitations to both procedures. The Friedwald procedure can be used on frozen sera but requires 3 ml sera. In contrast, the electrophoresis system must be used with fresh serum but requires only 50 μl serum and the electrophoretic slides may be quantitatively analyzed several years retrospectively.

AbstractOutcomes for older adults with acute myelogenous leukemia (AML) are poor due to both disease and host-related factors. In this phase 2 study, we tested the oral farnesyltransferase inhibitor tipifarnib in 158 older adults with previously untreated, poor-risk AML. The median age was 74 years, and a majority of patients had antecedent myelodysplastic syndrome. Complete remission (CR) was achieved in 22 patients (14%); partial remission or hematologic improvement occurred in 15 patients, for an overall response rate of 23%. The median duration of CR was 7.3 months and the median survival of complete responders was 18 months. Adverse karyotype, age 75 years or older, and poor performance status correlated negatively with survival. Early death in the absence of progressive disease was rare, and drug-related nonhematologic serious adverse events were observed in 74 patients (47%). Inhibition of farnesylation of the surrogate protein HDJ-2 occurred in the large majority of marrow samples tested. Baseline levels of phosphorylated mitogen-activated protein kinase and AKT did not correlate with clinical response. Tipifarnib is active and well tolerated in older adults with poor-risk AML and may impart a survival advantage in those patients who experience a clinical response.

Although osteoporosis has traditionally been considered a disease of women, men also incur substantial bone loss with aging, and elderly men have age-specific hip fracture incidence rates and vertebral fracture prevalence rates that are at least half those in women. Early postmenopausal bone loss (which results in the syndrome of type I osteoporosis) is due to the direct skeletal consequences of estrogen deficiency, manifested by an increase in bone resorption without an adequate increase in bone formation. Recent evidence indicates that even late postmenopausal bone loss (type II or ‘senile’ osteoporosis) in women may be due to estrogen deficiency. In particular, the late consequences of estrogen deficiency in elderly women result in abnormalities in calcium homeostasis and increases in parathyroid hormone secretion, leading to increased bone resorption and bone loss. The etiology of bone loss in aging men has remained relatively unclear. Recent evidence from a male deficient in estrogen receptor-alpha and in two males with aromatase deficiency indicate that estrogen may play a significant role in bone metabolism in men. Moreover, several large epidemiologic studies have found that bone mineral density correlates better with serum estrogen than testosterone in aging men. Thus estrogen deficiency may lead to bone loss in men.

In seven strains of cultured normal human osteoblast-like cells, a mean of 1615 molecules of tritium-labeled 17β-estradiol per cell nucleus could be bound to specific nuclear sites. The nuclear binding of the labeled steroid was temperature-dependent, steroid-specific, saturable, and cell type-specific. These are characteristics of biologically active estrogen receptors. Pretreatment with 10 nanomolar estradiol in vitro increased the specific nuclear binding of progesterone in four of six cell strains, indicating an induction of functional progesterone receptors. RNA blot analysis demonstrated the presence of messenger RNA for the human estrogen receptor. The data suggest that estrogen acts directly on human bone cells through a classical estrogen receptor-mediated mechanism.

Abstract A leading theory suggests that decreasing activity and muscle mass is the main cause of age-related bone loss. However, in a population-based study of 375 women and 325 men (age, 21–97 years), we failed to find a close correspondence between these variables and changes in bone strength with aging. Introduction: It has been suggested that bone strength is homeostatically adapted to habitual skeletal loading conditions and that bone loss could, therefore, result simply from age-related reductions in physical activity and muscle mass, but this notion has not been explored in detail. Materials and Methods: In a stratified random sample of Rochester, MN, women and men 21–97 years of age, indices of bone strength, flexural rigidity (EI), and axial rigidity (EA) were estimated from central QCT measurements at the femoral neck and lumbar spine and pQCT measurements at the ultradistal radius, whereas habitual skeletal loading was assessed using lean body mass, total skeletal muscle mass (TSM), body weight, and physical activity. Using regression analysis, we tested the hypothesis (Ho) that bone strength per unit load did not vary with age. Results and Conclusions: In these cross-sectional data, the null hypothesis of no age-related change was rejected in 72% of the strength-to-load ratios tested. For example, the ratio of femoral neck EI to TSM increased by 0.19%/year in women (p =0.008) and by 0.49%/year in men (p < 0.001). There was no close correspondence between changes in habitual load and changes in bone strength, nor any consistent pattern. Moreover, interindividual variation in the strength-to-load ratios was substantial. These data suggest that the notion of reduced skeletal loading as the primary basis for age-related bone loss is oversimplified.

Abstract We used QCT scans obtained in 687 men and women, 21–97 years of age, to estimate the factor of risk for vertebral fracture, Φvert, defined as the ratio of spinal loading to vertebral strength. With age, vertebral strength declined and Φvert increased significantly more in women than men. Age- and sex-specific differences in Φvert closely resembled previously reported vertebral fracture incidence. Introduction: Despite the high prevalence of vertebral fractures, little is known about the interaction between spinal loading and vertebral fragility. Materials and Methods: We assessed the ratio of spinal loading to vertebral strength (i.e., the factor of risk, Φvert) in an age- and sex-stratified population-based sample of 700 women and men 21–97 years of age. We measured volumetric BMD (vBMD, mg/cm3) and cross-sectional area (CSA, cm2) of the midvertebral bodies of L1–L3 using QCT and computed vertebral compressive strength from these data using engineering beam theory. A biomechanical model of the trunk was used to estimate compressive forces applied to the L3 vertebral body during standing, bending forward, and bending forward while lifting 10 kg. The factor of risk for fracture, Φvert, was computed as the ratio of spinal compressive force to vertebral strength for each activity. Results: Men had a higher vertebral strength at all ages, largely because of their greater CSA. Whereas both sexes exhibited a marked decline in vertebral compressive strength with age (p < 0.001), the decline was greater in women than men (−43% versus −31%, p = 0.008). Compressive forces on L3 were greater in men than women, because of their greater body weight and height. For both sexes, forces during bending and lifting were 8-fold higher than those experienced during upright standing. For all activities, Φvert increased with age, but significantly more so in women than men (p < 0.001). For bending and lifting, Φvert-bending exceeded 1.0 in 30% of women and 12% of men ≥50 years of age, values that are similar to the reported frequency of vertebral fracture. Conclusion: These findings illustrate potential mechanisms underlying vertebral fractures and provide strong rationale for further evaluation of this QCT-based biomechanical approach for assessment of fracture risk.

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease. This paper is part of the special issue of OMICS on data standards.

Purpose The purpose of this study was to determine whether an algorithm that recommended individualized changes in therapy would help providers to change therapy appropriately and improve glycemic control in their patients. Methods The algorithm recommended specific doses of oral agents and insulin based on a patient's medications and glucose or A1C levels at the time of the visit. The prospective observational study analyzed the effect of the algorithm on treatment decisions and A1C levels in patients with type 2 diabetes. Results The study included 1250 patients seen in pairs of initial and follow-up visits during a 7-month baseline and/or a subsequent 7-month algorithm period. The patients had a mean age of 62 years, body mass index of 33 kg/m2, duration of diabetes of 10 years, were 94% African American and 71% female, and had average initial A1C level of 7.7%. When the algorithm was available, providers were 45% more likely to intensify therapy when indicated (P = .005) and increased therapy by a 20% greater amount (P < .001). A1C level at follow-up was 90% more likely to be <7% in the algorithm group, even after adjusting for differences in age, sex, body mass index, race, duration of diabetes and therapy, glucose, and A1C level at the initial visit (P < .001). Conclusions Use of an algorithm that recommends patient-specific changes in diabetes medications improves both provider behavior and patient A1C levels and should allow quantitative evaluation of provider actions for that provider's patients.