Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells.

Local (cell-level) signaling environments, regulated by autocrine and paracrine signaling, and modulated by cell organization, are hypothesized to be fundamental stem cell fate control mechanisms used during development. It has, however, been challenging to demonstrate the impact of cell-level organization on stem cell fate control and to relate stem cell fate outcomes to autocrine and paracrine signaling. We address this fundamental problem using a combined in silico and experimental approach in which we directly manipulate, using laminar fluid flow, the local impact of endogenously secreted gp130-activating ligands and their activation of signal transducer and activator of transcription3 (STAT3) signaling in mouse embryonic stem cells (mESC). Our model analysis predicted that flow-dependent changes in autocrine and paracrine ligand binding would impact heterogeneity in cell- and colony-level STAT3 signaling activation and cause a gradient of cell fate determination along the direction of flow. Interestingly, analysis also predicted that local cell density would be inversely proportional to the degree to which endogenous secretion contributed to cell fate determination. Experimental validation using functional activation of STAT3 by secreted factors under microfluidic perfusion culture demonstrated that STAT3 activation and consequently mESC fate were manipulable by flow rate, position in the flow field, and local cell organization. As a unique demonstration of how quantitative control of autocrine and paracrine signaling can be integrated with spatial organization to elicit higher order cell fate effects, this work provides a general template to investigate organizing principles due to secreted factors.

Empagliflozin Reduces Liver Fat in Individuals With and Without Diabetes.

OBJECTIVE: To examine the effect of empagliflozin on liver fat content in individuals with and without type 2 diabetes (T2D) and the relationship between the decrease in liver fat and other metabolic actions of empagliflozin. RESEARCH DESIGN AND METHODS: Thirty individuals with T2D and 27 without were randomly assigned to receive in double-blind fashion empagliflozin or matching placebo (2:1 ratio) for 12 weeks. Participants underwent 75-g oral glucose tolerance testing and measurement of liver fat content with MRS before therapy and at study end. Hepatic glucose production before the start of therapy was measured with 3-3H-glucose. RESULTS: Empagliflozin caused an absolute reduction of 2.39% ± 0.79% in liver fat content compared with an increase of 0.91% ± 0.64% in participants receiving placebo (P < 0.007 with ANOVA). The decrease in liver fat was comparable in both individuals with diabetes and those without (2.75% ± 0.81% and 1.93% ± 0.78%, respectively; P = NS). The decrease in hepatic fat content caused by empagliflozin was strongly correlated with baseline liver fat content (r = -0.62; P < 0.001), decrease in body weight (r = 0.53; P < 0.001), and improvement in insulin sensitivity (r = -0.51; P < 0.001) but was not related to the decrease in fasting plasma glucose or HbA1c or the increase in hepatic glucose production. CONCLUSIONS: Empagliflozin is effective in reducing liver fat content in individuals with and without T2D. The decrease in liver fat content is independent of the decrease in plasma glucose concentration and is strongly related to the decrease in body weight and improvement in insulin sensitivity.

Rational bioprocess design for human pluripotent stem cell expansion and endoderm differentiation based on cellular dynamics.

We present a predictive bioprocess design strategy employing cell- and molecular-level analysis of rate-limiting steps in human pluripotent stem cell (hPSC) expansion and differentiation, and apply it to produce definitive endoderm (DE) progenitors using a scalable directed-differentiation technology. We define a bioprocess optimization parameter (L; targeted cell Loss) and, with quantitative cell division tracking and fate monitoring, identify and overcome key suspension bioprocess bottlenecks. Adapting process operating conditions to pivotal parameters (single cell survival and growth rate) in a cell-line-specific manner enabled adherent-equivalent expansion of hPSCs in feeder- and matrix-free defined-medium suspension culture. Predominantly instructive differentiation mechanisms were found to underlie a subsequent 18-fold expansion, during directed differentiation, to high-purity DE competent for further commitment along pancreatic and hepatic lineages. This study demonstrates that iPSC expansion and differentiation conditions can be prospectively specified to guide the enhanced production of target cells in a scale-free directed differentiation system.

Caffeine accelerates absorption and enhances the analgesic effect of acetaminophen.

The aim of this study was to determine the analgesic effect of acetaminophen compared to a combination of both caffeine and acetaminophen or caffeine alone using tonic and phasic pain stimulation. Twenty-four subjects were treated orally with 1000 mg acetaminophen, 130 mg caffeine, and a combination of both in a 4-way crossover, double-blind, placebo-controlled study. Pharmacokinetics and analgesic effects were assessed by means of an experimental pain model based on pain-related cortical potentials after phasic stimulation of the nasal mucosa with CO(2) and based on pain ratings after tonic stimulation with dry air. Analgesic effects of acetaminophen and acetaminophen plus caffeine but not caffeine alone caused a significant reduction of pain-related cortical potentials beginning 30 minutes after medication. The combination demonstrated an enhanced effect throughout the observation time up to 3 hours. Caffeine accelerated acetaminophen absorption, indicated by enhanced early AUCs. Significant analgesic effects of the combination on tonic pain ratings were found throughout the observation time as compared to acetaminophen and placebo. In this study, caffeine enhanced and prolonged the analgesic activity of acetaminophen.

Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks.

The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance, while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell-surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFNγ, Neurturin (Nrtn), and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.

Heterogeneous cellular environments modulate one-hit neuronal death kinetics.

We recently demonstrated that cell loss kinetics in diverse forms of neurodegeneration (ND) suggests a universal death switch mechanism in which each cell is at a constant risk to initiate apoptosis. We proposed that mutant and injured neurons exist in a viable state typified by an increased risk of initiating death processes [Clarke, Collins, Leavitt, Andrews, Hayden, Lumsden, McInnes, A one-hit model of cell death in inherited neuronal degenerations, Nature 406 (2000) 195-199]. To date, however, measurements of cell death risk have been available only as averages across the affected cell population. Here we develop and apply a method of death kinetic analysis in which the risk factors vary across the neuronal population, as for example due to regional heterogeneities in the cellular microenvironment. We find that most cases of ND for which cell loss data has been obtained are better explained by death risks that vary from cell to cell, compared to death risk that is constant across the neuronal population. Strikingly, a common form of the frequency distribution defining the death risk heterogeneity is shared across most of these cases. This first characterization of the kinetic heterogeneity in one-hit neuronal death, therefore, suggests that the wide variety of ND now known may share mechanisms through which regional differences in the cellular microenvironment modulate the kinetics of cell loss.

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death II: transition state metastability.

This is the second of two papers in which we study a mathematical model of cytoskeleton-induced neuron death. Recent evidence indicates that aggravated assembly or destruction of the cytoskeleton can trigger programmed death in neurons, by mechanisms as yet poorly understood. In our model, assembly control of the neuronal cytoskeleton interacts with both cellular stress levels and cytosolic free radical concentrations to trigger neurodegeneration. This trigger mechanism is further modulated by a diffusible toxic factor released from dying neurons. In the companion report we established that the model relates the observed general patterns of neuron decline to specific scales of cytoskeleton reorganization and cell-cell interaction strength. In this paper we study the transit of neurons through states intermediate between initial viability and cell death in our model. We find that the stochastic flow of neuron fate, from viability to cell death, self-organizes into two distinct temporal phases. There is a rapid relaxation of the initial neuron population to a more disordered phase that is long-lived, or metastable, with respect to the time scales of change in single cells. Strikingly, cellular egress from this metastable phase follows the one-hit kinetic pattern of exponential decline now established as a principal hallmark of cell death in neurodegenerative disorders. Intermediate state metastability may therefore be an important element in the systems biology of one-hit neurodegeneration.

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death I: cell-fate arrival times.

Much experimental evidence shows that the cytoskeleton is a downstream target and effector during cell death in numerous neurodegenerative diseases, including Parkinson's, Huntington's, and Alzheimer's diseases. However, recent evidence indicates that cytoskeletal dysfunction can also trigger neuronal death, by mechanisms as yet poorly understood. This is the first of two papers in which we study a mathematical model of cytoskeleton-induced neuron death. In our model, assembly control of the neuronal cytoskeleton interacts with both cellular stress levels and cytosolic free radical concentrations to trigger neurodegeneration. This trigger mechanism is further modulated by the presence of cell interactions in the form of a diffusible toxic factor released by dying neurons. We find that, consistent with empirical observations, our model produces one-hit exponential and sigmoid patterns of cell dropout. In all cases, cell dropout is exponential-tailed and described accurately by a gamma distribution. The transition between exponential and sigmoidal is gradual, and determined by a synergetic interaction between the magnitude of fluctuations in cytoskeleton assembly control and by the degree of cell coupling. We conclude that a single mechanism involving neuron interactions and fluctuations in cytoskeleton assembly control is compatible with the experimentally observed range of neuronal attrition kinetics.

Scale-free neurodegeneration: cellular heterogeneity and the stretched exponential kinetics of cell death.

Neurodegenerative disorders are an insidious group of diseases characterized by severe physical and cognitive effects that often have devastating consequences for the lives of affected individuals and their families. One feature common to a significant proportion of these diseases is that affected neurons commit to undergoing an active form of degeneration known as programmed cell death, or apoptosis. Although intense effort over the past several years has resulted is a remarkable increase in our understanding of the molecular events involved in neurodegeneration, our knowledge regarding the cellular and tissue properties that determine the temporal patterns of neuronal attrition is limited. We recently demonstrated that neurodegenerative kinetics in various diseases fit well to exponential decay functions, and proposed a universal one-hit switch mechanism in which mutant and injured neurons exist in a viable state characterized by an increased but constant risk of initiating apoptosis (Nature, 406, p. 195). Here we show that a heavy-tailed stretched exponential function is better able to account for neurodegenerative kinetic data. Moreover, normalization of all available data according to their corresponding best-fit stretched exponential parameters suggest that the generalized model is consistent with a universal mechanism of neuronal cell death that is greatly improved over the constant risk model. In contrast to the original model in which all cells exhibit an identical risk of initiating apoptosis, the stretched exponential model is consistent with each neuron experiencing a constant risk that is different from that experienced by other cells in the degenerating population, perhaps due to spatial differences in the cellular microenvironment. Intriguingly, the predicted distribution of risk across the cell population can be fit by a power-law function, further suggesting that scale-free properties of degenerating neuronal tissues might act as potent regulators of the kinetics of cell death in neural tissue.

Photoreceptor death: spatiotemporal patterns arising from one-hit death kinetics and a diffusible cell death factor.

Retinitis pigmentosa (RP) is an inherited disease affecting approximately 1:4000 individuals in North America. It is characterized clinically by the gradual apoptotic death of photoreceptor cells that occurs nonuniformly across the surface of the retina. Recently, it has been demonstrated that the time of death of many individual photoreceptors is random, a fact that must be reconciled with the spatiotemporal patterns of photoreceptor degeneration that are observed in patients with RP. One possible explanation is that a diffusible toxic factor is released by dying photoreceptors and induces adjacent cells to likewise undergo apoptosis. To determine if such a mechanism can result in patchy distributions of photoreceptor death, as frequently observed in RP patients, we studied cell attrition produced by a bistable biochemical switch in an idealized one-dimensional retina. We found that with a reasonable choice of parameter values, our model was able to produce patterns of cell death resembling those observed in RP. In the context of this model, patches on the order of histologically observable size could develop from a single release event, but their rates of formation were independent of the concentration of toxic factor released. Instead, factor concentration affected the overall rate of cell death, the number of degenerating patches, and their distribution across the retina.