Citations

Insulin secretion from the 2,000–3,000 β-cells in an islet is a highly synchronized activity with discharge of insulin in coordinate secretory bursts at approximately 4-min intervals. Insulin secretion progressively declines in type 2 diabetes and following islet transplantation. Both are characterized by the presence of islet amyloid derived from islet amyloid polypeptide (IAPP). In the present studies, we examined the action of extracellular human IAPP (h-IAPP) on morphology and function of human islets. Because oligomers of h-IAPP are known to cause membrane disruption, we questioned if application of h-IAPP oligomers to human islets would lead to disruption of islet architecture (specifically cell-to-cell adherence) and a decrease in coordinate function (e.g., increased entropy of insulin secretion and diminished coordinate secretory bursts). Both hypotheses are affirmed, leading to a novel hypothesis for impaired insulin secretion in type 2 diabetes and following islet transplantation, specifically disrupted cell-to-cell adherence in islets through the actions of membrane-disrupting IAPP oligomers.

Serotonin (5-HT) is one of the key mediators of gut motility, secretion and sensation. Most 5-HT is localized in the gastrointestinal tract. Particularly important for gut function and regulation are the 5-HT1P, 5-HT3and 5-HT4receptors. These receptors have been the focus of research evaluating the pathophysiologic mechanisms of irritable bowel syndrome (IBS) as well as targets for the development of novel agents to treat irritable bowel syndrome. Alosetron is one of three 5-HT3antagonists currently available. The other two, ondansetron and granisetron, are primarily used in the treatment of chemotherapy-induced nausea and vomiting. Alosetron, which slows gut transit, has been approved for the treatment of severe diarrhea-predominant IBS (IBS-D) in women. This review will examine the common, yet therapeutically challenging, disorder IBS, as well as the role of alosetron in the treatment of IBS-D.

IBM Systems and Technology Group uses operations research models and methods extensively for solving large-scale supply chain optimization (SCO) problems for planning its extended enterprise semiconductor supply chain. The large-scale nature of these problems necessitates the use of computationally efficient solution methods. However, the complexity of the models makes developing robust solution methods a challenge. We developed a mixed-integer programming (MIP) model and supporting heuristics for optimizing IBM’s semiconductor supply chain. We designed three heuristics, driven by practical applications, for capturing the discrete aspects of the MIP. We leverage the model structure to overcome computational hurdles resulting from the large-scale problem. IBM uses the model and method daily for operational and strategic planning decisions and has saved substantial costs.

AbstractA role for genetic susceptibility in non-Hodgkin lymphoma (NHL) is supported by the accumulating evidence of common genetic variations altering NHL risk. However, the pattern of NHL heritability remains poorly understood. We conducted a pooled analysis of 10 211 NHL cases and 11 905 controls from the International Lymphoma Epidemiology Consortium (InterLymph) to evaluate NHL risk among those with hematopoietic malignancies in first-degree relatives. Odds ratios (ORs) and 95% confidence intervals (CIs) of NHL and its subtypes were estimated from unconditional logistic regression models with adjustment for confounders. NHL risk was elevated for individuals who reported first-degree relatives with NHL (OR = 1.5; 95% CI = 1.2-1.9), Hodgkin lymphoma (OR = 1.6; 95% CI = 1.1-2.3), and leukemia (OR = 1.4; 95% CI = 1.2-2.7). Risk was highest among individuals who reported a brother with NHL (OR = 2.8; 95% CI = 1.6-4.8) and was consistent for all NHL subtypes evaluated. If a first-degree relative had Hodgkin lymphoma, NHL risk was highest if the relative was a parent (OR = 1.7; 95% CI = 1.0-2.9). If a first-degree relative had leukemia, NHL risk was highest among women who reported a sister with leukemia (OR = 3.0; 95% CI = 1.6-5.6). The pattern of NHL heritability appeared to be uniform across NHL subtypes, but risk patterns differed by specific hematopoietic malignancies and the sex of the relative, revealing critical clues to disease etiology.

Background— Aortic valve calcification (AVC) is considered degenerative. Recent data suggested links to atherosclerosis or coronary disease (CAD). Methods and Results— AVC and coronary artery calcifications (CAC) were prospectively assessed by Electron-Beam-Computed-Tomography in 262 population-based research participants ≥60 years. AVC was frequent (27%) with aging ( P <0.01) and in men ( P <0.05). AVC was associated with diabetes, hypertension, higher body-mass-index, and serum glucose (all P <0.05). AVC was a marker of higher prevalence ( P <0.01) and severity of CAD (CAC score: 441±802 versus 265±566, P <0.05) independently of age. After follow-up of 3.8±0.9 years, AVC score increased (94±271 versus 54±173, P <0.01, +11±32 U/year), faster with higher baseline AVC score ( P <0.01). Compared with participants remaining free of AVC, de novo acquisition of AVC was associated with higher LDL-cholesterol (141±31 versus 121±27 mg/dL, P <0.05) and faster CAC progression (+78±87 versus +28±47 U/year, P <0.05). In multivariate analysis, LDL-cholesterol independently determined AVC acquisition while higher baseline AVC scores determined faster progression of existing AVC. Conclusion— In the population, AVC is frequent with aging and atherosclerotic risk factors. AVC is a marker of subclinical CAD. AVC is progressive, appearing de novo with progressive atherosclerosis whereas established AVC progresses independently of atherosclerotic risk factors and faster with increasing initial AVC loads.

Abstract The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.