Low intense physical exercise in normobaric hypoxia leads to more weight loss in obese people than low intense physical exercise in normobaric sham hypoxia

Training in mild to moderate hypoxia (14–17% O2 in breathing air) and extended resting in moderate hypoxia (9–13% O2) have been shown to have effects in animals and humans on lipid and glucose metabolism, appetite loss, and, in part, on body weight. The causality for these effects is not yet known in detail, and the available data in humans from high-altitude and low-pressure chamber studies are scarce. New technical developments by German companies in the production of artificial climates with normobaric hypoxic conditions in larger rooms at reasonable energy costs allow now to perform hypoxia weight loss studies in obese humans with stable experimental conditions and protocols with a sham hypoxia control. Thirty-two obese people were recruited for a mild intense training study in normobaric hypoxia (15 vol.% O2) and normoxia/sham hypoxia (20.1 vol.% O2). Twenty of these [mean age 47.6 years, mean body mass index (BMI) 33.1, 16 m, 4 f) were willing to follow up on an 8-week, three times per week, 90-min low intense physical exercise in their individual fat burning mode, which has been determined by an exercise testing with spiro-ergometry upfront. The subjects were evenly randomized into a hypoxia and sham hypoxia group. The difference of the two groups in weight loss and changes in HBa1C values were analyzed before and after the training period. No nutritional diet was applied. Subjects in the hypoxia group in mean lost significantly more weight than in the sham hypoxia group (Δ1.14 kg vs Δ0.03 kg; p = 0.026). This resulted in a tendency to reduce the BMI more in the hypoxia group (p = 0.326). In the mean, there was no HbA1C exceeding normal values (mean 5.67 and 5.47%), and the HbA1C stayed basically unchanged after the 8-week training. Mild physical exercise three times per week for 90 min in normobaric hypoxia for 8 weeks led to significantly greater weight loss in obese persons than the exercise in sham hypoxia in this, to our knowledge, first sham hypoxia controlled study

SRFR1 Negatively Regulates Plant NB-LRR Resistance Protein Accumulation to Prevent Autoimmunity

Plant defense responses need to be tightly regulated to prevent auto-immunity, which is detrimental to growth and development. To identify negative regulators of Resistance (R) protein-mediated resistance, we screened for mutants with constitutive defense responses in the npr1-1 background. Map-based cloning revealed that one of the mutant genes encodes a conserved TPR domain-containing protein previously known as SRFR1 (SUPPRESSOR OF rps4-RLD). The constitutive defense responses in the srfr1 mutants in Col-0 background are suppressed by mutations in SNC1, which encodes a TIR-NB-LRR (Toll Interleukin1 Receptor-Nucleotide Binding-Leu-Rich Repeat) R protein. Yeast two-hybrid screens identified SGT1a and SGT1b as interacting proteins of SRFR1. The interactions between SGT1 and SRFR1 were further confirmed by co-immunoprecipitation analysis. In srfr1 mutants, levels of multiple NB-LRR R proteins including SNC1, RPS2 and RPS4 are increased. Increased accumulation of SNC1 is also observed in the sgt1b mutant. Our data suggest that SRFR1 functions together with SGT1 to negatively regulate R protein accumulation, which is required for preventing auto-activation of plant immunity

Expression Profiling Reveals Novel Hypoxic Biomarkers in Peripheral Blood of Adult Mice Exposed to Chronic Hypoxia

Hypoxia induces a myriad of changes including an increase in hematocrit due to erythropoietin (EPO) mediated erythropoiesis. While hypoxia is of importance physiologically and clinically, lacunae exist in our knowledge of the systemic and temporal changes in gene expression occurring in blood during the exposure and recovery from hypoxia. To identify these changes expression profiling was conducted on blood obtained from cohorts of C57Bl-10 wild type mice that were maintained at normoxia (NX), exposed for two weeks to normobaric chronic hypoxia (CH) or two weeks of CH followed by two weeks of normoxic recovery (REC). Using stringent bioinformatic cut-offs (0% FDR, 2 fold change cut-off), 230 genes were identified and separated into four distinct temporal categories. Class I) contained 1 transcript up-regulated in both CH and REC; Class II) contained 202 transcripts up-regulated in CH but down-regulated after REC; Class III) contained 9 transcripts down-regulated both in CH and REC; Class IV) contained 18 transcripts down-regulated after CH exposure but up-regulated after REC. Profiling was independently validated and extended by analyzing expression levels of selected genes as novel biomarkers from our profile (e.g. spectrin alpha-1, ubiquitin domain family-1 and pyrroline-5-carboxylate reductase-1) by performing qPCR at 7 different time points during CH and REC. Our identification and characterization of these genes define transcriptome level changes occurring during chronic hypoxia and normoxic recovery as well as novel blood biomarkers that may be useful in monitoring a variety of physiological and pathological conditions associated with hypoxia

Intracellular Water Exchange for Measuring the Dry Mass, Water Mass and Changes in Chemical Composition of Living Cells

We present a method for direct non-optical quantification of dry mass, dry density and water mass of single living cells in suspension. Dry mass and dry density are obtained simultaneously by measuring a cell’s buoyant mass sequentially in an H[subscript 2]O-based fluid and a D[subscript 2]O-based fluid. Rapid exchange of intracellular H[subscript 2]O for D[subscript 2]O renders the cell’s water content neutrally buoyant in both measurements, and thus the paired measurements yield the mass and density of the cell’s dry material alone. Utilizing this same property of rapid water exchange, we also demonstrate the quantification of intracellular water mass. In a population of E. coli, we paired these measurements to estimate the percent dry weight by mass and volume. We then focused on cellular dry density – the average density of all cellular biomolecules, weighted by their relative abundances. Given that densities vary across biomolecule types (RNA, DNA, protein), we investigated whether we could detect changes in biomolecular composition in bacteria, fungi, and mammalian cells. In E. coli, and S. cerevisiae, dry density increases from stationary to exponential phase, consistent with previously known increases in the RNA/protein ratio from up-regulated ribosome production. For mammalian cells, changes in growth conditions cause substantial shifts in dry density, suggesting concurrent changes in the protein, nucleic acid and lipid content of the cell.National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)National Institutes of Health (U.S.) (Center for Cell Division Process Grant P50GM6876)National Institutes of Health (U.S.) (Contract R01CA170592)United States. Army Research Office (Institute for Collaborate Biotechnologies Contract W911NF-09-D-0001

MOS11: A New Component in the mRNA Export Pathway

Nucleocytoplasmic trafficking is emerging as an important aspect of plant immunity. The three related pathways affecting plant immunity include Nuclear Localization Signal (NLS)–mediated nuclear protein import, Nuclear Export Signal (NES)–dependent nuclear protein export, and mRNA export relying on MOS3, a nucleoporin belonging to the Nup107–160 complex. Here we report the characterization, identification, and detailed analysis of Arabidopsis modifier of snc1, 11 (mos11). Mutations in MOS11 can partially suppress the dwarfism and enhanced disease resistance phenotypes of snc1, which carries a gain-of-function mutation in a TIR-NB-LRR type Resistance gene. MOS11 encodes a conserved eukaryotic protein with homology to the human RNA binding protein CIP29. Further functional analysis shows that MOS11 localizes to the nucleus and that the mos11 mutants accumulate more poly(A) mRNAs in the nucleus, likely resulting from reduced mRNA export activity. Epistasis analysis between mos3-1 and mos11-1 revealed that MOS11 probably functions in the same mRNA export pathway as MOS3, in a partially overlapping fashion, before the mRNA molecules pass through the nuclear pores. Taken together, MOS11 is identified as a new protein contributing to the transfer of mature mRNA from the nucleus to the cytosol

ENHANCING THE PERFORMANCE OF THE WALL-FOLLOWING ROBOT BASED ON FLC-GA

Determination of the improper speed of the wall-following robot will produce a wavy motion. This common problem can be solved by adding a Fuzzy Logic Controller (FLC) to the system. The usage of FLC is very influential on the performance of the wall-following robot. Accuracy in the determination of speed is largely based on the setting of the membership function that becomes the value of its input. So manual setting on membership function can still be enhanced by approaching the certain optimization method. This paper describes an optimization method based on Genetic Algorithm (GA). It is used to improving the ability of FLC to control the wall-following robot controlled by FLC. To provide clarity, the wall-following robot that controlled using an FLC with manual settings will be simulated and compared with the performance of wall-following robots controlled by a fuzzy logic controller optimized by a Genetic Algorithm (FLC-GA). According to comparative results, the proposed method has been showing effectiveness in terms of stability indicated by a small error

A MAPAEKF-SLAM ALGORITHM WITH RECURSIVE MEAN AND COVARIANCE OF PROCESS AND MEASUREMENT NOISE STATISTIC

The most popular filtering method used for solving a Simultaneous Localization and Mapping is the Extended Kalman Filter. Essentially, it requires prior stochastic knowledge both the process and measurement noise statistic. In order to avoid this requirement, these noise statistics have been defined at the beginning and kept to be fixed for the whole process. Indeed, it will satisfy the desired robustness in the case of simulation. Oppositely, due to the continuous uncertainty affected by the dynamic system under time integration, this manner is strongly not recommended. The reason is, improperly defined noise will not only degrade the filter performance but also might lead the filter to divergence condition. For this reason, there has been a strong manner well-termed as an adaptive-based strategy that commonly used to equip the classical filter for having an ability to approximate the noise statistic. Of course, by knowing the closely responsive noise statistic, the robustness and accuracy of an EKF can increase. However, most of the existed Adaptive-EKF only considered that the process and measurement noise statistic are characteristically zero-mean and responsive covariances. Accordingly, the robustness of EKF can still be enhanced. This paper presents a proposed method named as a MAPAEKF-SLAM algorithm used for solving the SLAM problem of a mobile robot, Turtlebot2. Sequentially, a classical EKF was estimated using Maximum a Posteriori. However, due to the existence of unobserved value, EKF was also smoothed one time based on the fixed-interval smoothing method. This smoothing step aims to keep-up the derivation process under MAP creation. Realistically, this proposed method was simulated and compared to the conventional one. Finally, it has been showing better accuracy in terms of Root Mean Square Error (RMSE) of both Estimated Map Coordinate (EMC) and Estimated Path Coordinate (EPC)