Effect of mechanomyography as a biofeedback method to enhance muscle relaxation and performance

The purpose of the study was to examine the potential for using the mechanomyographic (MMG) signal as a biofeedback method to enhance muscular relaxation and to improve performance during forearm flexion repetitions to fatigue. Twelve adult (mean +/- SD; age: 22.0 +/- 1.1 years) moderately trained subjects (weight: 82.3 +/- 29.2 kg; height: 165.7 +/- 49.0 cm) were instructed to relax the biceps brachii muscle using MMG biofeedback (BIO) provided by viewing a computer screen graphically displaying the MMG signal and then without using MMG biofeedback (NOBIO). Electromyographic (EMG) and MMG signals were detected midway over the biceps brachii during the relaxation protocol. In subsequent visits to the laboratory, subjects performed as many repetitions as possible at 85% of 1 repetition maximum with BIO and NOBIO using the seated preacher curl exercise. Two-way (biofeedback x gender) mixed factorial analyses of variance revealed significantly (p < 0.05) lower MMG (mean +/- SEM; BIO = 0.6 +/- 0.1 mV; NOBIO = 1.1 +/- 0.2 mV) and EMG amplitudes (BIO = 6.6 +/- 0.6 microV; NOBIO = 9.4 +/- 1.4 microV) for BIO when subjects were instructed to relax the biceps brachii muscle. There was no significant difference in the number of forearm flexion repetitions performed for BIO (mean +/- SD; 7.9 +/- 0.4 reps) vs. NOBIO (8.1 +/- 0.6 reps). The results of the present study revealed that using MMG as a biofeedback technique can enhance the development of muscle relaxation, but is not useful in delaying fatigue during forearm flexion repetitions. Our results may have been influenced by a relatively short training phase designed to teach subjects to use the MMG signal as a biofeedback method. Future studies are needed to determine whether MMG biofeedback can be used for other purposes. If MMG is found to be useful as a biofeedback method, it has some distinct practical advantages over EMG that the strength and conditioning athlete and professional may find appealing.     

Minimizing the overlap problem in protein NMR: a computational framework for precision amino acid labeling

MOTIVATION: Recent advances in cell-free protein expression systems allow specific labeling of proteins with amino acids containing stable isotopes ((15)N, (13) C and (2)H), an important feature for protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. Given this labeling ability, we present a mathematical optimization framework for designing a set of protein isotopomers, or labeling schedules, to reduce the congestion in the NMR spectra. The labeling schedules, which are derived by the optimization of a cost function, are tailored to a specific protein and NMR experiment. RESULTS: For 2D (15)N-(1)H HSQC experiments, we can produce an exact solution using a dynamic programming algorithm in under 2 h on a standard desktop machine. Applying the method to a standard benchmark protein, calmodulin, we are able to reduce the number of overlaps in the 500 MHz HSQC spectrum from 10 to 1 using four samples with a true cost function, and 10 to 4 if the cost function is derived from statistical estimates. On a set of 448 curated proteins from the BMRB database, we are able to reduce the relative percent congestion by 84.9% in their HSQC spectra using only four samples. Our method can be applied in a high-throughput manner on a proteomic scale using the server we developed. On a 100-node cluster, optimal schedules can be computed for every protein coded for in the human genome in less than a month. AVAILABILITY: A server for creating labeling schedules for (15)N-(1)H HSQC experiments as well as results for each of the individual 448 proteins used in the test set is available at http://nmr.proteomics.ics.uci.edu.     

The ancestor of the <Emphasis Type="Italic">Paulinella</Emphasis> chromatophore obtained a carboxysomal operon by horizontal gene transfer from a <Emphasis Type="Italic">Nitrococcus</Emphasis>-like γ-proteobacterium

Background  

Paulinella chromatophora is a freshwater filose amoeba with photosynthetic endosymbionts (chromatophores) of cyanobacterial origin that are closely related to free-living Prochlorococcus and Synechococcus species (PS-clade). Members of the PS-clade of cyanobacteria contain a proteobacterial form 1A RubisCO (ribulose-1,5-bisphosphate carboxylase/oxygenase) that was acquired by horizontal gene transfer (HGT) of a carboxysomal operon. In rDNA-phylogenies, the Paulinella chromatophore diverged basal to the PS-clade, raising the question whether the HGT occurred before or after the split of the chromatophore ancestor.     

Rheological characterization of neutral and anionic polysaccharides with reduced mucociliary transport rates

The purpose of this research was to compare the viscoelastic properties of several neutral and anionic polysaccharide polymers with their mucociliary transport rates (MTR) across explants of ciliated bovine tracheal tissue to identify rheologic parameters capable of predicting the extent of reduction in mucociliary transport. The viscoelastic properties of the polymer gels and gels mixed with mucus were quantified using controlled stress rheometry. In general, the anionic polysaccharides were more efficient at decreasing the mucociliary transport rate than were the neutral polymers, and a concentration threshold, where no further decreases in mucociliary transport occurred with increasing polymer concentration, was observed for several of the neutral polysaccharides. No single rheologic parameter (ν, G′, G″, tan δ, G^*) was a good predictor of the extent of mucociliary transport reduction, but a combination of the apparent viscosity (ν), tangent to the phase angle (tan δ), and complex modulus (G^*) was found to be useful in the identification of formulations capable of decreasing MTR. The relative values of each of the rheologic parameters were unique for each polymer, yet once the relationships between the rheologic parameters and mucociliary transport rate reduction were determined, formulations capable of resisting mucociliary clearance could be rapidly optimized. Published: April 20, 2007     

Role of cyclooxygenase-2 in Trypanosoma cruzi survival in the early stages of parasite host-cell interaction

Chagas disease, caused by the intracellular protozoan Trypanosoma cruzi, is a serious health problem in Latin America. During this parasitic infection, the heart is one of the major organs affected. The pathogenesis of tissue remodelling, particularly regarding cardiomyocyte behaviour after parasite infection and the molecular mechanisms that occur immediately following parasite entry into host cells are not yet completely understood. When cells are infected with T. cruzi, they develop an inflammatory response, in which cyclooxygenase-2 (COX-2) catalyses rate-limiting steps in the arachidonic acid pathway. However, how the parasite interaction modulates COX-2 activity is poorly understood. In this study, the H9c2 cell line was used as our model and we investigated cellular and biochemical aspects during the initial 48 h of parasitic infection. Oscillatory activity of COX-2 was observed, which correlated with the control of the pro-inflammatory environment in infected cells. Interestingly, subcellular trafficking was also verified, correlated with the control of Cox-2 mRNA or the activated COX-2 protein in cells, which is directly connected with the assemble of stress granules structures. Our collective findings suggest that in the very early stage of the T. cruzi-host cell interaction, the parasite is able to modulate the cellular metabolism in order to survives.     

Mir-190b negatively contributes to the Trypanosoma cruzi- infected cell survival by repressing PTEN protein expression

Chagas disease, which is caused by the intracellular protozoanTrypanosoma cruzi, is a serious health problem in Latin America. The heart is one of the major organs affected by this parasitic infection. The pathogenesis of tissue remodelling, particularly regarding cardiomyocyte behaviour after parasite infection, and the molecular mechanisms that occur immediately following parasite entry into host cells are not yet completely understood. Previous studies have reported that the establishment of parasitism is connected to the activation of the phosphatidylinositol-3 kinase (PI3K), which controls important steps in cellular metabolism by regulating the production of the second messenger phosphatidylinositol-3,4,5-trisphosphate. Particularly, the tumour suppressor PTEN is a negative regulator of PI3K signalling. However, mechanistic details of the modulatory activity of PTEN on Chagas disease have not been elucidated. To address this question, H9c2 cells were infected with T. cruzi Berenice 62 strain and the expression of a specific set of microRNAs (miRNAs) were investigated. Our cellular model demonstrated that miRNA-190b is correlated to the decrease of cellular viability rates by negatively modulating PTEN protein expression in T. cruzi-infected cells.     

Head-to-tail regulation is critical for the in vivo function of myosin V

Cell organization requires regulated cargo transport along cytoskeletal elements. Myosin V motors are among the most conserved organelle motors and have been well characterized in both yeast and mammalian systems. Biochemical data for mammalian myosin V suggest that a head-to-tail autoinhibitory interaction is a primary means of regulation, but the in vivo significance of this interaction has not been studied. Here we generated and characterized mutations in the yeast myosin V Myo2p to reveal that it is regulated by a head-to-tail interaction and that loss of regulation renders the myosin V constitutively active. We show that an unregulated motor is very deleterious for growth, resulting in severe defects in Myo2-mediated transport processes, including secretory vesicle transport, mitochondrial inheritance, and nuclear orientation. All of the defects associated with motor misregulation could be rescued by artificially restoring regulation. Thus, spatial and temporal regulation of myosin V in vivo by a head-to-tail interaction is critical for the normal delivery functions of the motor.     

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

Background

The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information.

Methods

The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability.

Results

Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.     

Ligand-dependent differences in estrogen receptor beta-interacting proteins identified in lung adenocarcinoma cells corresponds to estrogenic responses

Background

A recent epidemiological study demonstrated a reduced risk of lung cancer mortality in breast cancer patients using antiestrogens. These and other data implicate a role for estrogens in lung cancer, particularly nonsmall cell lung cancer (NSCLC). Approximately 61% of human NSCLC tumors express nuclear estrogen receptor β (ERβ); however, the role of ERβ and estrogens in NSCLC is likely to be multifactorial. Here we tested the hypothesis that proteins interacting with ERβ in human lung adenocarcinoma cells that respond proliferatively to estradiol (E₂) are distinct from those in non-E₂-responsive cells.

Methods

FLAG affinity purification of FLAG-ERβ-interacting proteins was used to isolate ERβ-interacting proteins in whole cell extracts from E₂ proliferative H1793 and non-E₂-proliferative A549 lung adenocarcinoma cell lines. Following trypsin digestion, proteins were identified using liquid chromatography electrospray ionization tandem mass spectrometry (LC-MS/MS). Proteomic data were analyzed using Ingenuity Pathway Analysis. Select results were confirmed by coimmunoprecipitation.

Results

LC-MS/MS identified 27 non-redundant ERβ-interacting proteins. ERβ-interacting proteins included hsp70, hsp60, vimentin, histones and calmodulin. Ingenuity Pathway Analysis of the ERβ-interacting proteins revealed differences in molecular and functional networks between H1793 and A549 lung adenocarcinoma cells. Coimmunoprecipitation experiments in these and other lung adenocarcinoma cells confirmed that ERβ and EGFR interact in a gender-dependent manner and in response to E₂ or EGF. BRCA1 interacted with ERβ in A549 cell lines and in human lung adenocarcinoma tumors, but not normal lung tissue.

Conclusion

Our results identify specific differences in ERβ-interacting proteins in lung adenocarcinoma cells corresponding to ligand-dependent differences in estrogenic responses.

     

A theoretical entropy score as a single value to express inhibitor selectivity

Background  

Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.