Temporal Monitoring of Differentiated Human Airway Epithelial Cells Using Microfluidics

The airway epithelium is exposed to a variety of harmful agents during breathing and appropriate cellular responses are essential to maintain tissue homeostasis. Recent evidence has highlighted the contribution of epithelial barrier dysfunction in the development of many chronic respiratory diseases. Despite intense research efforts, the responses of the airway barrier to environmental agents are not fully understood, mainly due to lack of suitable in vitro models that recapitulate the complex in vivo situation accurately. Using an interdisciplinary approach, we describe a novel dynamic 3D in vitro model of the airway epithelium, incorporating fully differentiated primary human airway epithelial cells at the air-liquid interface and a basolateral microfluidic supply of nutrients simulating the interstitial flow observed in vivo. Through combination of the microfluidic culture system with an automated fraction collector the kinetics of cellular responses by the airway epithelium to environmental agents can be analysed at the early phases for the first time and with much higher sensitivity compared to common static in vitro models. Following exposure of primary differentiated epithelial cells to pollen we show that CXCL8/IL–8 release is detectable within the first 2h and peaks at 4–6h under microfluidic conditions, a response which was not observed in conventional static culture conditions. Such a microfluidic culture model is likely to have utility for high resolution temporal profiling of toxicological and pharmacological responses of the airway epithelial barrier, as well as for studies of disease mechanisms.     

Elucidating the Foundations of Statistical Inference with 2 x 2 Tables

To many, the foundations of statistical inference are cryptic and irrelevant to routine statistical practice. The analysis of 2 x 2 contingency tables, omnipresent in the scientific literature, is a case in point. Fisher''s exact test is routinely used even though it has been fraught with controversy for over 70 years. The problem, not widely acknowledged, is that several different p-values can be associated with a single table, making scientific inference inconsistent. The root cause of this controversy lies in the table''s origins and the manner in which nuisance parameters are eliminated. However, fundamental statistical principles (e.g., sufficiency, ancillarity, conditionality, and likelihood) can shed light on the controversy and guide our approach in using this test. In this paper, we use these fundamental principles to show how much information is lost when the tables origins are ignored and when various approaches are used to eliminate unknown nuisance parameters. We present novel likelihood contours to aid in the visualization of information loss and show that the information loss is often virtually non-existent. We find that problems arising from the discreteness of the sample space are exacerbated by p-value-based inference. Accordingly, methods that are less sensitive to this discreteness - likelihood ratios, posterior probabilities and mid-p-values - lead to more consistent inferences.     

Distinct tubulin genes are differentially expressed during barley grain development

Tubulins, as major components involved in the organization of microtubules, play an important role in plant development. We describe here the expression profiles of all known α-tubulin (TUA), β-tubulin (TUB) and γ-tubulin (TUG) genes of barley ( Hordeum vulgare ), involving eight newly identified TUB sequences, five established TUA genes and one TUG gene. Macroarray and Northern blot-based expression patterns in the pericarp, endosperm and embryo were obtained over the course of the development of the grain between anthesis and maturation. These revealed that the various tubulin genes differed in their levels of expression, and to some extent were tissue specific. Two expression peaks were detected in the developing endosperm. The first and more prominent peak, at 2 days after flowering, included expression of almost all the tubulin genes. These tubulins are thought to be involved in mitoses during the formation of the syncytial endosperm. The second, less pronounced but more extended, peak included only some of the tubulin genes ( HvTUA3 , HvTUB1 and HvTUG ) and might be associated with the cell wall organization in aleurone and starchy endosperm. The HvTUA5 gene is expressed only in embryo of the developing grain and may be associated with shoot establishment. The expression profiles of the tubulin folding cofactors HvTFC A and HvTFC B as well as small G-protein HvArl2 genes were almost perfectly correlated with the global levels of tubulin mRNA, implying that they have a role in the control of the polymerization of α/β-tubulin heterodimers.     

Interaction of poly(l-lysines) with negatively charged membranes: an FT-IR and DSC study

The influence of the binding of poly(l-lysine) (PLL) to negatively charged membranes containing phosphatidylglycerols (PG) was studied by DSC and FT-IR spectroscopy. We found a general increase in the main transition temperature as well as increase in hydrophobic order of the membrane upon PLL binding. Furthermore we observed stronger binding of hydration water to the lipid head groups after PLL binding. The secondary structure of the PLL after binding was studied by FT-IR spectroscopy. We found that PLL binds in an α-helical conformation to negatively charged DPPG membranes or membranes with DPPG-rich domains. Moreover we proved that PLL binding induces domain formation in the gel state of mixed DPPC/DPPG or DMPC/DPPG membranes as well as lipid remixing in the liquid–crystalline state. We studied these effects as a function of PLL chain length and found a significant dependence of the secondary structure, phase transition temperature and domain formation capacity on PLL chain length and also a correlation between the peptide secondary structure and the phase transition temperature of the membrane. We present a system in which the membrane phase transition triggers a highly cooperative secondary structure transition of the membrane-bound peptide from α-helix to random coil. Dedicated to Prof. K. Arnold on the occasion of his 65th birthday.     

Phosphorylation at Ser244 by CK1 determines nuclear localization and substrate targeting of PKD2

Protein kinase D2 (PKD2), a member of the PKD family of serine/threonine kinases, is localized in various subcellular compartments including the nucleus where the kinase accumulates upon activation of G-protein-coupled receptors. We define three critical post-translational modifications required for nuclear accumulation of PKD2 in response to activation of the CCK2 receptor (CCK2R): phosphorylation at Ser706 and Ser710 within the activation loop by PKC eta leading to catalytic activity and phosphorylation at Ser244 within the zinc-finger domain, which is crucial for blocking nuclear export of active PKD2 by preventing its interaction with the Crm-1 export machinery. We identify CK1delta and epsilon as upstream activated kinases by CCK2R that phosphorylate PKD2 at Ser244. Moreover, nuclear accumulation of active PKD2 is a prerequisite for efficient phosphorylation of its nuclear substrate, HDAC7. Only nuclear, active PKD2 mediates CCK2R-induced HDAC7 phosphorylation and Nur77 expression. Thus, we define a novel, compartment-specific signal transduction pathway downstream of CCK2R that phosphorylates PKD2 at three specific sites, results in nuclear accumulation of the active kinase and culminates in efficient phosphorylation of nuclear PKD2 substrates in human gastric cancer cells.     

Modeling <Emphasis Type="Italic">Neisseria meningitidis</Emphasis> metabolism: from genome to metabolic fluxes

Background  

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years.     

Simulation of human atherosclerotic femoral plaque tissue: the influence of plaque material model on numerical results

Background

Due to the limited number of experimental studies that mechanically characterise human atherosclerotic plaque tissue from the femoral arteries, a recent trend has emerged in current literature whereby one set of material data based on aortic plaque tissue is employed to numerically represent diseased femoral artery tissue. This study aims to generate novel vessel-appropriate material models for femoral plaque tissue and assess the influence of using material models based on experimental data generated from aortic plaque testing to represent diseased femoral arterial tissue.

Methods

Novel material models based on experimental data generated from testing of atherosclerotic femoral artery tissue are developed and a computational analysis of the revascularisation of a quarter model idealised diseased femoral artery from a 90% diameter stenosis to a 10% diameter stenosis is performed using these novel material models. The simulation is also performed using material models based on experimental data obtained from aortic plaque testing in order to examine the effect of employing vessel appropriate material models versus those currently employed in literature to represent femoral plaque tissue.

Results

Simulations that employ material models based on atherosclerotic aortic tissue exhibit much higher maximum principal stresses within the plaque than simulations that employ material models based on atherosclerotic femoral tissue. Specifically, employing a material model based on calcified aortic tissue, instead of one based on heavily calcified femoral tissue, to represent diseased femoral arterial vessels results in a 487 fold increase in maximum principal stress within the plaque at a depth of 0.8 mm from the lumen.

Conclusions

Large differences are induced on numerical results as a consequence of employing material models based on aortic plaque, in place of material models based on femoral plaque, to represent a diseased femoral vessel. Due to these large discrepancies, future studies should seek to employ vessel-appropriate material models to simulate the response of diseased femoral tissue in order to obtain the most accurate numerical results.

     

Review and classification of variability analysis techniques with clinical applications

Background

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

Method

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

Results

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

Conclusions

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.