Some Factors That May Determine the Frequency Response of Cells and Tissue to Applied Electrical and Mechanical Forces

This article has no abstract.     

Analysis of Factors That Determine Weight Gain during Smoking Cessation Therapy

Cigarette smokers are generally known to gain weight after quitting smoking, and such weight gain is thought to contribute to the worsening of glucose tolerance. While smoking cessation therapy such as nicotine replacement is useful to minimize post-cessation weight gain, substantial gain occurs even during the therapy. The purpose of the present study was to identify factors associated with weight gain during smoking cessation therapy. We evaluated 186 patients(132 males and 54 females)who visited our outpatient clinic for smoking cessation, and successfully achieved smoking abstinence. We performed gender-adjusted regression analysis for the rate of BMI increase from the beginning of cessation to 3 months after initiation. Furthermore, we performed multivariate analysis to investigate factors that determine the BMI increase after smoking cessation. The mean BMI significantly (p<0.0001) increased from 23.5±3.6 kg/m² at the initial consultation to 23.9±3.8 kg/m² at 3 months after the start of therapy. There was no significant difference in the extent of BMI increase between nicotine patch and varenicline therapy groups. Factors significantly correlated with the %BMI increase at 3 months after the start of therapy were triglyceride (p = 0.0006, βa = 0.260), high-density lipoprotein cholesterol (p = 0.0386, βa = −0.168), daily cigarette consumption (p = 0.0385, βa = 0.154), and the Fagerström Test for Nicotine Dependence (FTND) score (p = 0.0060, βa = 0.203). Stepwise multivariate analysis demonstrated that triglyceride and the FTND score were the factors determining the post-cessation BMI increase and that the FTND score was the strongest one. The present study demonstrated that smokers with a high FTND score are more likely to gain weight during smoking cessation therapy. Thus, smokers with a high nicotine dependency may require intervention against weight gain in the cessation clinic.     

Factors Other than the Glomerular Filtration Rate That Determine the Serum Beta-2-Microglobulin Level

Background

β2-microglobulin has been increasingly investigated as a diagnostic marker of kidney function and a prognostic marker of adverse outcomes. To date, non-renal determinants of β2-microglobulin levels have not been well described. Non-renal determinants are important for the interpretation and appraisal of the diagnostic and prognostic value of any endogenous kidney function marker.

Methods

This cross-sectional analysis was performed within the framework of the www.seniorlabor.ch study, which includes subjectively healthy individuals aged ≥60 years. Factors known or suspected to have a non-renal association with kidney function markers were investigated for a non-renal association with serum β2-microglobulin. As a marker of kidney function, the Berlin Initiative Study equation 2 for the estimation of the estimated glomerular filtration rate (eGFR_BIS2) in the elderly was employed.

Results

A total of 1302 participants (714 females and 588 males) were enrolled in the study. The use of a multivariate regression model adjusting for age, gender and kidney function (eGFR_BIS2) revealed age, male gender, and C-reactive protein level to be positively associated with β2-microglobulin levels. In addition, there was an inverse non-renal relationship between systolic blood pressure, total cholesterol and current smoking status. No association with markers of diabetes mellitus, body stature, nutritional risk, thyroid function or calcium and phosphate levels was observed.

Conclusions

Serum β2-microglobulin levels in elderly subjects are related to several non-renal factors. These non-renal factors are not congruent to those known from other markers (i.e. cystatin C and creatinine) and remind of classical cardiovascular risk factors.     

Identification of Crucial Amino Acids in Mouse Aldehyde Oxidase 3 That Determine Substrate Specificity

In order to elucidate factors that determine substrate specificity and activity of mammalian molybdo-flavoproteins we performed site directed mutagenesis of mouse aldehyde oxidase 3 (mAOX3). The sequence alignment of different aldehyde oxidase (AOX) isoforms identified variations in the active site of mAOX3 in comparison to other AOX proteins and xanthine oxidoreductases (XOR). Based on the structural alignment of mAOX3 and bovine XOR, differences in amino acid residues involved in substrate binding in XORs in comparison to AOXs were identified. We exchanged several residues in the active site to the ones found in other AOX homologues in mouse or to residues present in bovine XOR in order to examine their influence on substrate selectivity and catalytic activity. Additionally we analyzed the influence of the [2Fe-2S] domains of mAOX3 on its kinetic properties and cofactor saturation. We applied UV-VIS and EPR monitored redox-titrations to determine the redox potentials of wild type mAOX3 and mAOX3 variants containing the iron-sulfur centers of mAOX1. In addition, a combination of molecular docking and molecular dynamic simulations (MD) was used to investigate factors that modulate the substrate specificity and activity of wild type and AOX variants. The successful conversion of an AOX enzyme to an XOR enzyme was achieved exchanging eight residues in the active site of mAOX3. It was observed that the absence of the K889H exchange substantially decreased the activity of the enzyme towards all substrates analyzed, revealing that this residue has an important role in catalysis.     

Variation in Salamander Tail Regeneration Is Associated with Genetic Factors That Determine Tail Morphology

Very little is known about the factors that cause variation in regenerative potential within and between species. Here, we used a genetic approach to identify heritable genetic factors that explain variation in tail regenerative outgrowth. A hybrid ambystomatid salamander (Ambystoma mexicanum x A. andersoni) was crossed to an A. mexicanum and 217 offspring were induced to undergo metamorphosis and attain terrestrial adult morphology using thyroid hormone. Following metamorphosis, each salamander’s tail tip was amputated and allowed to regenerate, and then amputated a second time and allowed to regenerate. Also, DNA was isolated from all individuals and genotypes were determined for 187 molecular markers distributed throughout the genome. The area of tissue that regenerated after the first and second amputations was highly positively correlated across males and females. Males presented wider tails and regenerated more tail tissue during both episodes of regeneration. Approximately 66–68% of the variation in regenerative outgrowth was explained by tail width, while tail length and genetic sex did not explain a significant amount of variation. A small effect QTL was identified as having a sex-independent effect on tail regeneration, but this QTL was only identified for the first episode of regeneration. Several molecular markers significantly affected regenerative outgrowth during both episodes of regeneration, but the effect sizes were small (<4%) and correlated with tail width. The results show that ambysex and minor effect QTL explain variation in adult tail morphology and importantly, tail width. In turn, tail width at the amputation plane largely determines the rate of regenerative outgrowth. Because amputations in this study were made at approximately the same position of the tail, our results resolve an outstanding question in regenerative biology: regenerative outgrowth positively co-varies as a function of tail width at the amputation site.     

Identification of a Maize Locus That Modulates the Hypersensitive Defense Response,Using Mutant-Assisted Gene Identification and Characterization

Potentially useful naturally occurring genetic variation is often difficult to identify as the effects of individual genes are subtle and difficult to observe. In this study, a novel genetic technique called Mutant-Assisted Gene Identification and Characterization is used to identify naturally occurring loci modulating the hypersensitive defense response (HR) in maize. Mutant-Assisted Gene Identification and Characterization facilitates the identification of naturally occurring alleles underlying phenotypic variation from diverse germplasm, using a mutant phenotype as a “reporter.” In this study the reporter phenotype was caused by a partially dominant autoactive disease resistance gene, Rp1-D21, which caused HR lesions to form spontaneously all over the plant. Here it is demonstrated that the Rp1-D21 phenotype is profoundly affected by genetic background. By crossing the Rp1-D21 gene into the IBM mapping population, it was possible to map and identify Hrml1 on chromosome 10, a locus responsible for modulating the HR phenotype conferred by Rp1-D21. Other loci with smaller effects were identified on chromosomes 1 and 9. These results demonstrate that Mutant-Assisted Gene Identification and Characterization is a viable approach for identifying naturally occurring useful genetic variation.POTENTIALLY useful naturally occurring genetic variation is often difficult to identify as the effects of individual genes are subtle and difficult to observe. Furthermore, so many different alleles are available that it is a major challenge just to sift through the enormous diversity available. To this end, we recently conceptualized a simple yet effective method to discover and characterize variation present naturally in plant germplasm (Johal et al. 2008). This method, Mutant-Assisted Gene Identification and Characterization, makes use of a mutant phenotype for a gene affecting the trait of interest as a reporter to discover and analyze relevant, interacting genes present naturally in diverse germplasm. Mutant-Assisted Gene Identification and Characterization involves crossing a mutant to diverse germplasm and then evaluating the mutant progeny for transgressive changes (both suppressed and severe) in the mutant phenotype(s). If the mutation is recessive, the population needs to be advanced to the F₂ generation to be able to detect and analyze such variation. However, for a dominant or partially dominant mutant, evaluations can be made immediately in the F₁ to discover lines that contain suppressors or enhancers of the trait (mutation) under study. Mutant F₁ progenies from such crosses can then be propagated further to identify, map, and clone genes/QTL that affect the trait positively or negatively. In the case of maize and other species for which genetically characterized mapping populations are available, modifying loci can be rapidly mapped by crossing a mutant line to each member of a mapping population and evaluating the resulting F₁ families. In this study we provide a proof-of-concept for the Mutant-Assisted Gene Identification and Characterization technique, using it to identify loci involved in the defense response of maize.Plants are constantly exposed to numerous potential pathogens with diverse modes of attack. Nevertheless, it is rather rare to see plants succumbing to disease. One key reason for this is the presence of a highly effective and inducible defense system, a major component of which is the hypersensitive response (HR). HR is usually associated with a specific recognition event and is activated after other nonspecific resistance mechanisms have been overcome or evaded (see Bent and Mackey 2007). Although it was initially coined to refer to the rapid collapse of cells at the site of infection, over the years the term HR has been used to refer to both cell death and the associated induction of a number of other defense responses, including the accumulation of phytoalexins and pathogenesis-related (PR) proteins at the site of infection, to name a few (Mur et al. 2007). Reactive oxygen species such as superoxide and H₂O₂ appear to be causally involved in cell death underlying the HR response (Jones and Dangl 2006).HR is under the control of a subset of disease-resistance genes, commonly referred to as R genes. These R genes specifically recognize matching avirulence (Avr) effectors from the pathogen. Many R genes encode products containing a nucleotide-binding site (NBS) domain in the middle of the protein and a leucine-rich repeat (LRR) domain at the C-terminal end (Bent and Mackey 2007). R proteins are involved both in the recognition of the pathogen and the subsequent induction of the HR response. How R proteins remain in a quiescent but “vigilant” state remains to be established. Certain mutations in R genes have been found that abolish their dependence on AVR proteins for activation. Such aberrant R genes mostly behave as dominant or partially dominant alleles and trigger the HR constitutively in the absence of the pathogen (Hu et al. 1996; Zhang et al. 2003; Dodds et al. 2006). Two consequences of such “autoactive” or “ectopically active” R genes are a massive induction of cell death and the consequential stunting of the organism (Dodds et al. 2006). Although autoactive R genes have been found to exist in many plant species, the first few examples came from the maize Rp1 locus, which confers race-specific resistance to common rust, caused by Puccinia sorghi (Hu et al. 1996). Such autoactive R genes can be used to investigate HR genetics and etiology in the absence of confounding effects from the pathogen and constitute an excellent candidate for analysis using Mutant-Assisted Gene Identification and Characterization.The details of the HR cell death reaction as well as the pathway(s) that link R gene activation with the HR remain unclear (Mur et al. 2007). Despite considerable research over the past decade, only a few components have been found thus far. Some of these, Ndr1, Eds1, Pad4, Rar1, and Sgt1, were identified in mutagenesis screens conducted to identify mutants that failed to undergo an HR reaction in response to infection by an avirulent pathogen (reviewed in Bent and Mackey 2007). A few others, RIN4, for example, were identified in yeast two-hybrid assays using an NBS–LRR protein as bait (Mackey et al. 2003). Recently, an Arabidopsis gain-of-function mutant that carries a point mutation in an R gene analog (a gene with the structure of an R gene but not known to be involved in resistance to any pathogen) was used to isolate a few more potential genes in the HR pathway in a second site suppressor approach following mutagenesis with ethane methyl sulfonate (EMS) (Palma et al. 2005; Zhang and Li 2005; Goritschnig et al. 2007). A problem with approaches based on intentional mutagenesis is that they fail to uncover genes that have either redundant or essential functions. One way to avoid this problem would be to seek naturally occurring allelic variants affecting HR. Such natural variation is pervasive in all species, being generated and selected for over millions of years of evolution.Although natural variation has served as a constant provider of the R genes in all plant species, natural variability has not been tapped as a tool for understanding other aspects of the disease-resistance response (Holub 2007). The Rp1-D21 gene is an autoactive allele from the maize Rp1 disease-resistance locus that initiates HR randomly all over the plant (Pryor 1993; Collins et al. 1999; Sun et al. 2001). Our objective for this study was to use the Rp1-D21 gene phenotype as a test case for the Mutant-Assisted Gene Identification and Characterization approach. We show here that enormous variation exists in the maize germplasm that is capable of affecting the HR response positively or negatively and we identify loci that modulate expression of the HR phenotype segregating in the well-known Intermated B73 × Mo17 (IBM) advanced intercross line (AIL) population (Coe et al. 2002; Lee et al. 2002). This constitutes the first demonstration of the utility of the Mutant-Assisted Gene Identification and Characterization approach—an approach that is likely to prove widely applicable.     

Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks

The poor response to the combined antiviral therapy of pegylated alfa-interferon and ribavarin for hepatitis C virus (HCV) infection may be linked to mutations in the viral envelope gene E1E2 (env), which can result in escape from the immune response and higher efficacy of viral entry. Mutations that result in failure of therapy most likely require compensatory mutations to achieve sufficient change in envelope structure and function. Compensatory mutations were investigated by determining positions in the E1E2 gene where amino acids (aa) covaried across groups of individuals. We assessed networks of covarying positions in E1E2 sequences that differentiated sustained virological response (SVR) from non-response (NR) in 43 genotype 1a (17 SVR), and 49 genotype 1b (25 SVR) chronically HCV-infected individuals. Binary integer programming over covariance networks was used to extract aa combinations that differed between response groups. Genotype 1a E1E2 sequences exhibited higher degrees of covariance and clustered into 3 main groups while 1b sequences exhibited no clustering. Between 5 and 9 aa pairs were required to separate SVR from NR in each genotype. aa in hypervariable region 1 were 6 times more likely than chance to occur in the optimal networks. The pair 531–626 (EI) appeared frequently in the optimal networks and was present in 6 of 9 NR in one of the 1a clusters. The most frequent pairs representing SVR were 431–481 (EE), 500–522 (QA) in 1a, and 407–434 (AQ) in 1b. Optimal networks based on covarying aa pairs in HCV envelope can indicate features that are associated with failure or success to antiviral therapy.     

Identification of Pharmacological Modulators of HMGB1-Induced Inflammatory Response by Cell-Based Screening

High mobility group box 1 (HMGB1), a highly conserved, ubiquitous protein, is released into the circulation during sterile inflammation (e.g. arthritis, trauma) and circulatory shock. It participates in the pathogenesis of delayed inflammatory responses and organ dysfunction. While several molecules have been identified that modulate the release of HMGB1, less attention has been paid to identify pharmacological inhibitors of the downstream inflammatory processes elicited by HMGB1 (C23-C45 disulfide C106 thiol form). In the current study, a cell-based medium-throughput screening of a 5000+ compound focused library of clinical drugs and drug-like compounds was performed in murine RAW264.7 macrophages, in order to identify modulators of HMGB1-induced tumor-necrosis factor alpha (TNFα) production. Clinically used drugs that suppressed HMGB1-induced TNFα production included glucocorticoids, beta agonists, and the anti-HIV compound indinavir. A re-screen of the NIH clinical compound library identified beta-agonists and various intracellular cAMP enhancers as compounds that potentiate the inhibitory effect of glucocorticoids on HMGB1-induced TNFα production. The molecular pathways involved in this synergistic anti-inflammatory effect are related, at least in part, to inhibition of TNFα mRNA synthesis via a synergistic suppression of ERK/IκB activation. Inhibition of TNFα production by prednisolone+salbutamol pretreatment was also confirmed in vivo in mice subjected to HMGB1 injection; this effect was more pronounced than the effect of either of the agents administered separately. The current study unveils several drug-like modulators of HMGB1-mediated inflammatory responses and offers pharmacological directions for the therapeutic suppression of inflammatory responses in HMGB1-dependent diseases.     

Timing and Intensity of Light Correlate with Body Weight in Adults

Light exposure can influence sleep and circadian timing, both of which have been shown to influence weight regulation. The goal of this study was to evaluate the relationship between ambient light, sleep and body mass index. Participants included 54 individuals (26 males, mean age 30.6, SD = 11.7 years). Light levels, sleep midpoint and duration were measured with wrist actigraphy (Actiwatch-L) for 7 days. BMI was derived from self-reported height and weight. Caloric intake was determined from 7 days of food logs. For each participant, light and activity data were output in 2 minute epochs, smoothed using a 5 point (10 minute) moving average and then aggregated over 24 hours. The mean light timing above 500 lux (MLiT⁵⁰⁰) was defined as the average clock time of all aggregated data points above 500 lux. MLiT⁵⁰⁰ was positively correlated with BMI (r = 0.51, p<0.001), and midpoint of sleep (r = 0.47, p<0.01). In a multivariable linear regression model including MLiT⁵⁰⁰ and midpoint of sleep, MLiT⁵⁰⁰ was a significant predictor of BMI (B = 1.26 SE = 0.34, β = 0.53 p = 0.001, r ² _Δ = 0.22). Adjusting for covariates, MLiT⁵⁰⁰ remained an independent predictor of BMI (B = 1.28 SE = 0.36, β = 0.54, p = 0.002, r ² _Δ = 0.20). The full model accounted for 34.7% of the variance in BMI (p = 0.01). Exposure to moderate levels of light at biologically appropriate times can influence weight, independent of sleep timing and duration.     

A Mechanistic Model of the Regulation of Division Timing by the Circadian Clock in Cyanobacteria

The cyanobacterium Synechococcus elongatus possesses a circadian clock in the form of a group of proteins whose concentrations and phosphorylation states oscillate with daily periodicity under constant conditions. The circadian clock regulates the cell cycle such that the timing of the cell divisions is biased toward certain times during the circadian period, but the mechanism underlying this phenomenon remains unclear. Here, we propose a mechanism in which a protein limiting for division accumulates at a rate proportional to the cell volume growth and is modulated by the clock. This “modulated rate” model, in which the clock signal is integrated over time to affect division timing, differs fundamentally from the previously proposed “gating” concept, in which the clock is assumed to suppress divisions during a specific time window. We found that although both models can capture the single-cell statistics of division timing in S. elongatus, only the modulated rate model robustly places divisions away from darkness during changes in the environment. Moreover, within the framework of the modulated rate model, existing experiments on S. elongatus are consistent with the simple mechanism that division timing is regulated by the accumulation of a division limiting protein in a phase with genes whose activity peaks at dusk.     

Structural Analysis to Determine the Core of Hypoxia Response Network

The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network''s dynamics. The question that begs for an answer is how to identify the core that is representative of a network''s dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent.     

计算识别microRNA及其靶基因

小RNA的发现为基因调控系统研究提供了新的方向。在多数物种中已经发现了大量的小RNA。这一领域已经成为了近来研究的热点,在研究起始阶段,计算学方法已经成为实验研究中不可或缺的工具,许多发现是由生物学实验与计算学方法共同合作来完成的。在这篇综述中,我们总结了前人关于小RNA及其靶基因识别的理论知识。最后,讨论了关于预测小RNA及其靶基因的计算学方法和相关软件。