A mechanistic model of small intestinal starch digestion and glucose uptake in the cow

The high contribution of postruminal starch digestion (up to 50%) to total-tract starch digestion on energy-dense, starch-rich diets demands that limitations to small intestinal starch digestion be identified. A mechanistic model of the small intestine was described and evaluated with regard to its ability to simulate observations from abomasal carbohydrate infusions in the dairy cow. The 7 state variables represent starch, oligosaccharide, glucose, and pancreatic amylase in the intestinal lumen, oligosaccharide and glucose in the unstirred water layer at the intestinal wall, and intracellular glucose of the enterocyte. Enzymatic hydrolysis of starch was modeled as a 2-stage process involving the activity of pancreatic amylase in the lumen and of oligosaccharidase at the brush border of the enterocyte confined within the unstirred water layer. The Na+-dependent glucose transport into the enterocyte was represented along with a facilitative glucose transporter 2 transport system on the basolateral membrane. The small intestine is subdivided into 3 main sections, representing the duodenum, jejunum, and ileum for parameterization. Further subsections are defined between which continual digesta flow is represented. The model predicted nonstructural carbohydrate disappearance in the small intestine for cattle unadapted to duodenal infusion with a coefficient of determination of 0.92 and a root mean square prediction error of 25.4%. Simulation of glucose disappearance for mature Holstein heifers adapted to various levels of duodenal glucose infusion yielded a coefficient of determination of 0.81 and a root mean square prediction error of 38.6%. Analysis of model behavior identified limitations to the efficiency of small intestinal starch digestion with high levels of duodenal starch flow. Limitations to individual processes, particularly starch digestion in the proximal section of the intestine, can create asynchrony between starch hydrolysis and glucose uptake capacity

What Do Community Benefits Agreements Deliver? Evidence From Los Angeles

Problem, research strategy, and findings: Advocates of community benefits agreements (CBAs) between coalitions of nongovernmental organizations (NGOs) and real estate developers contend that CBAs promote public accountability and responsiveness to community concerns. This study assesses the Los Angeles Sports and Entertainment District (LASED) CBA, which scholars and practitioners have described as a model for such agreements. I assess compliance with key provisions of the agreement related to jobs, affordable housing, and parks and recreational facilities. I also assess whether compliance with these provisions has yielded benefits beyond those required under existing laws and regulations. I find that the parties to the agreement have technically complied with many, although arguably not all, of its provisions. But some of the provisions in the CBA are not legally binding, other provisions overlap with requirements that the developer would have had to satisfy even without the CBA, and some reports required by the CBA are unavailable. As a result, outcomes such as living wage jobs and funding for affordable housing units are not clearly attributable to the CBA; other outcomes, such as targeted hiring, are unknown due to a lack of relevant information.Takeaway for practice: Although CBAs may not fulfill all the claims that advocates make on their behalf, they can play important roles in community development by directing public and private spending to underserved neighborhoods. But collecting and verifying the relevant data may be challenging, even if reporting requirements are clearly spelled out in the CBA. As the complexity of a CBA increases, so do the challenges of assessing outcomes and assigning responsibility for those outcomes

From 1/f Noise to Multifractal Cascades in Heartbeat Dynamics

We explore the degree to which concepts developed in statistical physics can be usefully applied to physiological signals. We illustrate the problems related to physiologic signal analysis with representative examples of human heartbeat dynamics under healthy and pathologic conditions. We first review recent progress based on two analysis methods, power spectrum and detrended fluctuation analysis, used to quantify long-range power-law correlations in noisy heartbeat fluctuations. The finding of power-law correlations indicates presence of scale-invariant, fractal structures in the human heartbeat. These fractal structures are represented by self-affine cascades of beat-to-beat fluctuations revealed by wavelet decomposition at different time scales. We then describe very recent work that quantifies multifractal features in these cascades, and the discovery that the multifractal structure of healthy dynamics is lost with congestive heart failure. The analytic tools we discuss may be used on a wide range of physiologic signals

Beyond 1/f: Multifractality in Human Heartbeat Dynamics

Recent evidence suggests that physiological signals under healthy conditions may have a fractal temporal structure. We investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report on evidence for multifractality in a biological dynamical system -- the healthy human heartbeat. Further, we show that the multifractal character and nonlinear properties of the healthy heart rate are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure

The Operator Fejér-Riesz Theorem

The Fejér-Riesz theorem has inspired numerous generalizations in one and several variables, and for matrix- and operator-valued functions. This paper is a survey of some old and recent topics that center around Rosenblum’s operator generalization of the classical Fejér-Riesz theorem