Ferritin and Percent Transferrin Saturation Levels Predict Type 2 Diabetes Risk and Cardiovascular Disease Outcomes

Introduction: Type 2 diabetes (T2D) and cardiovascular disease (CVD) risk associate withferritin and percent transferrin saturation (%TS) levels. However, increased risk has been observed at levels considered within the “normal range” for these markers. Objective: To define normative ferritin and %TS levels associated with T2D and CVD risk. Methods: Six-monthly ferritin, %TS and hemoglobin levels from 1,277 iron reduction clinical trial participants with CVD (peripheral arterial disease, 37% diabetic) permitted pair-wise analysis using Loess Locally Weighted Smoothing plots. Curves showed continuous quantitative ferritin, hemoglobin (reflecting physiologic iron requirements), and %TS (reflecting iron transport and sequestration) levels over a wide range of values. Inflection points in the curves were compared to ferritin and %TS levels indicating increased T2D and CVD risk in epidemiologic and intervention studies. Results: Increasing ferritin up to about 80 ng/mL and %TS up to about 25% TS corresponded to increasing hemoglobin levels, and minimal T2D and CVD risk. Displaced Loess trajectories reflected lower hemoglobin levels in diabetics compared to non-diabetics. Ferritin levels up to about 100 ng/mL paralleled proportionately increasing %TS levels up to about 55%TS corresponding to further limitation of T2D and CVD risk. Ferritin levels over 100 ng/mL did not associate with hemoglobin levels and coincided with increased T2D and CVD risk. Conclusions: Recognition of modified normal ranges for ferritin from about 15 ng/mL up to about 80- 100 ng/mL and %TS from about 15% up to about 25-55% may improve the value of iron biomarkers to assess and possibly lower T2D and CVD risk

Downregulation of Cinnamyl-Alcohol Dehydrogenase in Switchgrass by RNA Silencing Results in Enhanced Glucose Release after Cellulase Treatment

Cinnamyl alcohol dehydrogenase (CAD) catalyzes the last step in monolignol biosynthesis and genetic evidence indicates CAD deficiency in grasses both decreases overall lignin, alters lignin structure and increases enzymatic recovery of sugars. To ascertain the effect of CAD downregulation in switchgrass, RNA mediated silencing of CAD was induced through Agrobacterium mediated transformation of cv. ‘‘Alamo’’ with an inverted repeat construct containing a fragment derived from the coding sequence of PviCAD2. The resulting primary transformants accumulated less CAD RNA transcript and protein than control transformants and were demonstrated to be stably transformed with between 1 and 5 copies of the TDNA. CAD activity against coniferaldehyde, and sinapaldehyde in stems of silenced lines was significantly reduced as was overall lignin and cutin. Glucose release from ground samples pretreated with ammonium hydroxide and digested with cellulases was greater than in control transformants. When stained with the lignin and cutin specific stain phloroglucinol- HCl the staining intensity of one line indicated greater incorporation of hydroxycinnamyl aldehydes in the lignin

Hydrodynamics of the Kuramoto-Sivashinsky Equation in Two Dimensions

The large scale properties of spatiotemporal chaos in the 2d Kuramoto-Sivashinsky equation are studied using an explicit coarse graining scheme. A set of intermediate equations are obtained. They describe interactions between the small scale (e.g., cellular) structures and the hydrodynamic degrees of freedom. Possible forms of the effective large scale hydrodynamics are constructed and examined. Although a number of different universality classes are allowed by symmetry, numerical results support the simplest scenario, that being the KPZ universality class.Comment: 4 pages, 3 figure

the relationship between alcohol consumption and vascular complications and mortality in individuals with type 2 diabetes

OBJECTIVE Moderate alcohol consumption has been associated with a reduced risk of mortality and coronary artery disease. The relationship between cardiovascular health and alcohol use in type 2 diabetes is less clear. The current study assesses the effects of alcohol use among participants in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified-Release Controlled Evaluation (ADVANCE) trial. RESEARCH DESIGN AND METHODS The effects of alcohol use were explored using Cox regression models, adjusted for potential confounders. The study end points were cardiovascular events (cardiovascular death, myocardial infarction, and stroke), microvascular complications (new or worsening nephropathy or retinopathy), and all-cause mortality. RESULTS During a median of 5 years of follow-up, 1,031 (9%) patients died, 1,147 (10%) experienced a cardiovascular event, and 1,136 (10%) experienced a microvascular complication. Compared with patients who reported no alcohol consumption, those who reported moderate consumption had fewer cardiovascular events (adjusted hazard ratio [aHR] 0.83; 95% CI 0.72–0.95; P = 0.008), less microvascular complications (aHR 0.85; 95% CI 0.73–0.99; P = 0.03), and lower all-cause mortality (aHR 0.87; 96% CI 0.75–1.00; P = 0.05). The benefits were particularly evident in participants who drank predominantly wine (cardiovascular events aHR 0.78, 95% CI 0.63–0.95, P = 0.01; all-cause mortality aHR 0.77, 95% CI 0.62–0.95, P = 0.02). Compared with patients who reported no alcohol consumption, those who reported heavy consumption had dose-dependent higher risks of cardiovascular events and all-cause mortality. CONCLUSION In patients with type 2 diabetes, moderate alcohol use, particularly wine consumption, is associated with reduced risks of cardiovascular events and all-cause mortality

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

Ears of the Armadillo: Global Health Research and Neglected Diseases in Texas

Neglected tropical diseases (NTDs) have\ud been recently identified as significant public\ud health problems in Texas and elsewhere in\ud the American South. A one-day forum on the\ud landscape of research and development and\ud the hidden burden of NTDs in Texas\ud explored the next steps to coordinate advocacy,\ud public health, and research into a\ud cogent health policy framework for the\ud American NTDs. It also highlighted how\ud U.S.-funded global health research can serve\ud to combat these health disparities in the\ud United States, in addition to benefiting\ud communities abroad

Prognostic capabilities of coronary computed tomographic angiography before non-cardiac surgery: Prospective cohort study

Objectives To determine if coronary computed tomographic angiography enhances prediction of perioperative risk in patients before non-cardiac surgery and to assess the preoperative coronary anatomy in patients who experience a myocardial infarction after non-cardiac surgery. Design Prospective cohort study. Setting 12 centers in eight countries. Participants 955 patients with, or at risk of, atherosclerotic disease who underwent non-cardiac surgery. Interventions Coronary computed tomographic angiography was performed preoperatively; clinicians were blinded to the results unless left main disease was suspected. Results were classified as normal, non-obstructive (<50% stenosis), obstructive (one or two vessels with ≥50% stenosis), or extensive obstructive (≥50% stenosis in two vessels including the proximal left anterior descending artery, three vessels, or left main). Main outcome measure Composite of cardiovascular death and non-fatal myocardial infarction within 30 days after surgery (primary outcome). This was the dependent variable in Cox regression. The independent variables were scores on the revised cardiac risk index and findings on coronary computed tomographic angiography. Results The primary outcome occurred in 74 patients (8%). The model that included both scores on the revised cardiac risk index and findings on coronary computed tomographic angiography showed that coronary computed tomographic angiography provided independent prognostic information (P=0.014; C index=0.66). The adjusted hazard ratios were 1.51 (95% confidence interval 0.45 to 5.10) for non-obstructive disease; 2.05 (0.62 to 6.74) for obstructive disease; and 3.76 (1.12 to 12.62) for extensive obstructive disease. For the model with coronary computed tomographic angiography compared with the model based on the revised cardiac risk index alone, with 30 day risk categories of <5%, 5-15%, and >15% for the primary outcome, the results of risk reclassification indicate that in a sample of 1000 patients that coronary computed tomographic angiography would have resulted appropriately in 17 net patients receiving a higher risk estimation among the 77 patients who would have experienced the primary outcome (P<0.001). Coronary computed tomographic angiography, however, would have resulted inappropriately in 98 net patients receiving a higher risk estimation, among the 923 patients who would not have experienced the primary outcome (P<0.001). Among patients who had a perioperative myocardial infarction, preoperative coronary anatomy showed extensive obstructive disease in 31% (22/71), obstructive disease in 41% (29/71), non-obstructive disease in 24% (17/71), and normal findings in 4% (3/71). Conclusions Though findings on coronary computed tomographic angiography can improve estimation of risk for patients who will experience perioperative cardiovascular death or myocardial infarction, findings are more than five times as likely to lead to an inappropriate overestimation of risk among patients who will not experience these outcomes. Perioperative myocardial infarction occurs across the spectrum of coronary artery disease, suggesting that there could be several pathophysiologic mechanisms

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154104/1/kampfner1996.pd