Nitrous oxide emission in an aerobic granulation sequencing batch airlift reactor at ambient temperatures

This study aims to investigate the nitrous oxide (N2O) emission in an aerobic granulation sequencing batch airlift reactor (SBAR) and the associated microbial community of aerobic granular sludge at ambient temperature (18±3)°C. After 48 days of operation, 1-2mm granules were obtained and excellent chemical oxygen demand (COD) and ammonium (NH4+-N) removal efficiencies were stably achieved. N2O concentration in the off gas was maximal at the beginning of the aerobic period and stabilized at a lower concentration after an initial peak. (0.60±0.17, n=3) % of the total nitrogen load to the SBAR was emitted as N2O. A dramatic change in the microbial community structure was noted between the initial seed sludge and the final mature aerobic granular sludge. Nitrosospira was identified to be the dominant ammonium oxidizing bacteria (AOB) which was attributed as the dominant source of N2O production in aerobic granular sludge by analysis of 16S rDNA sequences. © 2013 Elsevier Ltd

Urokinase plasminogen activator secreted by cancer-associated fibroblasts induces tumor progression via PI3K/AKT and ERK signaling in esophageal squamous cell carcinoma

published_or_final_versio

Epistatic Interactions Alter Dynamics of Multilocus Gene-for-Gene Coevolution

Fitness costs associated with resistance or virulence genes are thought to play a key role in determining the dynamics of gene-for-gene (GFG) host-parasite coevolution. However, the nature of interactions between fitness effects of multiple resistance or virulence genes (epistasis) has received less attention. To examine effects of the functional form of epistasis on the dynamics of GFG host-parasite coevolution we modified a classic multilocus GFG model framework. We show that the type of epistasis between virulence genes largely determines coevolutionary dynamics, and that coevolutionary fluctuations are more likely with acceleratingly costly (negative) than with linear or deceleratingly costly (positive) epistasis. Our results demonstrate that the specific forms of interaction between multiple resistance or virulence genes are a crucial determinant of host-parasite coevolutionary dynamics

Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant-pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the''Guard-Hypothesis,'' R proteins (the ``guards'') can sense modification of target molecules in the host (the ``guardees'') by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the ``guardee-effector'' interface for pathogen recognition, natural selection acts on the ``guard-guardee'' interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen

The addition of a pH-sensitive gel improves microemulsion stability for the targeted removal of colonic ammonia

<p>Abstract</p> <p>Background</p> <p>We prepared an oral W/O microemulsion for the removal of colonic ammonia (ME-RCA). The effect of this microemulsion was influenced by the digestion process in the gastrointestinal tract. In this paper, we aim to show that stability was improved by using a microemulsion-based gel for the removal of colonic ammonia (MBG-RCA).</p> <p>Methods</p> <p>MBG-RCA was prepared by adding sodium alginate to the ME-RCA. MBG-RCA and ME-RCA were passed through a simulated gastrointestinal environment, and the amount of colonic ammonia present was then determined by titration with a standard solution of hydrochloric acid. The pH of the gastrointestinal fluid was measured using a pH test paper and the size and form of the microemulsions were examined under the microscope. 18 healthy rats were randomly divided into three groups, fasted for 24 hours and allowed to drink normally. Three-way pipes were placed at the gastroduodenal junction in Group I, and at the terminal ileum in Group II. After the intragastric administration of ME-RCA, the stomach contents in Group I, the effluent from the terminal ileum in Group II and discharge from the anus in Group III were collected. The pH values of the gastrointestinal juice were measured by the pH test paper and those of the colon were determined by a universal indicator. These animal experiments were also used to test the effect of MBG-RCA.</p> <p>Results</p> <p>MBG-RCA showed a better removal rate of artificial colonic ammonia than ME-RCA (P < 0.05). The decrease in pH value of the artificial small intestinal fluid due to ME-RCA did not occur when MBG-RCA was used. In the simulated gastrointestinal process, MBG-RCA maintained greater stability and released the emulsion (ME-RCA) in the colonic fluid. In the gastrointestinal tract of normal SD rats, ME-RCA decreased in size and lost its stable form after entering the small intestine, while MBG-RCA remained stable and intact emulsion-drops were observed from the anus. Neither substance had any effect on the pH of the stomach or colon of normal rats (partly because normal rats were fasted for 24 hours and allowed to drink normally, which resulted in a low level of ammonia production in the colon). Unlike ME-RCA, MBG-RCA did not reduce the pH of the small intestine.</p> <p>Conclusions</p> <p>MBG-RCA was more stable in the gastrointestinal tract and more effective at removing colonic ammonia when a higher concentration of ammonia was present. This made it possible to achieve the targeted removal of colonic ammonia and is a promising method to prevent hepatic encephalopathy (HE) in future studies.</p

Robust Framework for PET Image Reconstruction Incorporating System and Measurement Uncertainties

In Positron Emission Tomography (PET), an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts

Use of dietary supplements in Olympic athletes is decreasing: a follow-up study between 2002 and 2009

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to assess the frequency of use of dietary supplements (DS) among large sample of elite Finnish athletes and to describe possible changes in dietary supplement use between the years 2002 and 2009.</p> <p>Methods</p> <p>A prospective follow-up study was conducted on Olympic athletes. The first survey was conducted on Olympic athletes in 2002 (N = 446) and the follow-up study was conducted between May 2008 and June 2009 (N = 372).</p> <p>Results</p> <p>In 2002, a total of 81% of the athletes used dietary supplements (a mean of 3.37 ± 3.06 DS per user) and in 2009, a total of 73% of the athletes (a mean of 2.60 ± 2.69 per DS user) used them. After adjusting for age-, sex- and sport type, the OR (95% confidence interval, CI) for use of any dietary supplement was significantly less in 2009 as compared with 2002 results (OR, 0.62; 95% CI, 0.43-0.90). Decrease in DS use was observed in all supplement subgroups (vitamins, minerals, nutritional supplements). Athletes in speed and power events and endurance events reported use of any dietary supplement significantly more often than team sport athletes both in 2002 and 2009. In year 2009, the frequency of all dietary supplement use increased when athlete's age increased and the increase was significant in older age groups: of the athletes under 21 years 63%, 21-24 years 83% and over 24 years 90% consumed nutritional supplements.</p> <p>Conclusions</p> <p>Based in our study, there seems to be a lowering trend of dietary supplement use among elite Finnish athletes although differences between sport subgroups and age groups are considerable.</p

Global parameter estimation methods for stochastic biochemical systems

<p>Abstract</p> <p>Background</p> <p>The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equation. As in other modelling frameworks, the accompanying rate constants are important for the end-applications like analyzing system properties (e.g. robustness) or predicting the effects of genetic perturbations. Prior knowledge of kinetic constants is usually limited and the model identification routine typically includes parameter estimation from experimental data. Although the subject of parameter estimation is well-established for deterministic models, it is not yet routine for the chemical master equation. In addition, recent advances in measurement technology have made the quantification of genetic substrates possible to single molecular levels. Thus, the purpose of this work is to develop practical and effective methods for estimating kinetic model parameters in the chemical master equation and other stochastic models from single cell and cell population experimental data.</p> <p>Results</p> <p>Three parameter estimation methods are proposed based on the maximum likelihood and density function distance, including probability and cumulative density functions. Since stochastic models such as chemical master equations are typically solved using a Monte Carlo approach in which only a finite number of Monte Carlo realizations are computationally practical, specific considerations are given to account for the effect of finite sampling in the histogram binning of the state density functions. Applications to three practical case studies showed that while maximum likelihood method can effectively handle low replicate measurements, the density function distance methods, particularly the cumulative density function distance estimation, are more robust in estimating the parameters with consistently higher accuracy, even for systems showing multimodality.</p> <p>Conclusions</p> <p>The parameter estimation methodologies described in this work have provided an effective and practical approach in the estimation of kinetic parameters of stochastic systems from either sparse or dense cell population data. Nevertheless, similar to kinetic parameter estimation in other modelling frameworks, not all parameters can be estimated accurately, which is a common problem arising from the lack of complete parameter identifiability from the available data.</p

Efficient Conversion of Astrocytes to Functional Midbrain Dopaminergic Neurons Using a Single Polycistronic Vector

Direct cellular reprogramming is a powerful new tool for regenerative medicine. In efforts to understand and treat Parkinson's Disease (PD), which is marked by the degeneration of dopaminergic neurons in the midbrain, direct reprogramming provides a valuable new source of these cells. Astrocytes, the most plentiful cells in the central nervous system, are an ideal starting population for the direct generation of dopaminergic neurons. In addition to their potential utility in cell replacement therapies for PD or in modeling the disease in vitro, astrocyte-derived dopaminergic neurons offer the prospect of direct in vivo reprogramming within the brain. As a first step toward this goal, we report the reprogramming of astrocytes to dopaminergic neurons using three transcription factors – ASCL1, LMX1B, and NURR1 – delivered in a single polycistronic lentiviral vector. The process is efficient, with 18.2±1.5% of cells expressing markers of dopaminergic neurons after two weeks. The neurons exhibit expression profiles and electrophysiological characteristics consistent with midbrain dopaminergic neurons, notably including spontaneous pacemaking activity, stimulated release of dopamine, and calcium oscillations. The present study is the first demonstration that a single vector can mediate reprogramming to dopaminergic neurons, and indicates that astrocytes are an ideal starting population for the direct generation of dopaminergic neurons

A Novel Biochemical Route for Fuels and Chemicals Production from Cellulosic Biomass

The conventional biochemical platform featuring enzymatic hydrolysis involves five key steps: pretreatment, cellulase production, enzymatic hydrolysis, fermentation, and product recovery. Sugars are produced as reactive intermediates for subsequent fermentation to fuels and chemicals. Herein, an alternative biochemical route is proposed. Pretreatment, enzymatic hydrolysis and cellulase production is consolidated into one single step, referred to as consolidated aerobic processing, and sugar aldonates are produced as the reactive intermediates for biofuels production by fermentation. In this study, we demonstrate the viability of consolidation of the enzymatic hydrolysis and cellulase production steps in the new route using Neurospora crassa as the model microorganism and the conversion of cellulose to ethanol as the model system. We intended to prove the two hypotheses: 1) cellulose can be directed to produce cellobionate by reducing β-glucosidase production and by enhancing cellobiose dehydrogenase production; and 2) both of the two hydrolysis products of cellobionate—glucose and gluconate—can be used as carbon sources for ethanol and other chemical production. Our results showed that knocking out multiple copies of β-glucosidase genes led to cellobionate production from cellulose, without jeopardizing the cellulose hydrolysis rate. Simulating cellobiose dehydrogenase over-expression by addition of exogenous cellobiose dehydrogenase led to more cellobionate production. Both of the two hydrolysis products of cellobionate: glucose and gluconate can be used by Escherichia coli KO 11 for efficient ethanol production. They were utilized simultaneously in glucose and gluconate co-fermentation. Gluconate was used even faster than glucose. The results support the viability of the two hypotheses that lay the foundation for the proposed new route