The rapid emergence of nonalcoholic fatty liver disease (NAFLD) as a cause of both liver‐related morbidity and mortality and cardiometabolic risk has led to the search for effective lifestyle ...strategies to reduce liver fat. Lifestyle intervention comprising dietary restriction in conjunction with increased physical activity has shown clear hepatic benefits when weight loss approximating 3%‐10% of body weight is achieved. Yet, the poor sustainability of weight loss challenges the current therapeutic focus on body weight and highlights the need for alternative strategies for NAFLD management. Epidemiologic data show an independent relationship between liver fat, physical activity, and fitness, and a growing body of longitudinal research demonstrates that increased physical activity participation per se significantly reduces hepatic steatosis and serum aminotransferases in individuals with NAFLD, independent of weight loss. Mechanistic insights to explain this interaction are outlined, and recommendations for the implementation of lifestyle intervention involving physical activity are discussed. In light of the often poor sustainability of weight loss strategies, and the viability of physical activity therapy, clinicians should assess physical fitness and physical activity habits, educate patients on the benefits of fitness outside of weight loss, and focus on behavior change which promotes physical activity adoption. (HEPATOLOGY 2010)
Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a ...cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.
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•Computational method to predict alternative splicing effects on molecular interactions•The method leverages a machine learning approach and shows superior accuracy•Large-scale application to study transcriptome of type 2 diabetes in mice•Easy-to-use Docker container and python script interface to use the method
Narykov et al. develops a sequence-based machine learning method that determines whether a protein-protein interaction can be disrupted by the alternatively spliced version of an interacting protein. Accurate identification of disrupted interactions due to alternative splicing can provide new insights into molecular mechanisms governing functional changes associated with a disease.
RNA sequencing (RNA-seq) is becoming a prevalent approach to quantify gene expression and is expected to gain better insights into a number of biological and biomedical questions compared to DNA ...microarrays. Most importantly, RNA-seq allows us to quantify expression at the gene or transcript levels. However, leveraging the RNA-seq data requires development of new data mining and analytics methods. Supervised learning methods are commonly used approaches for biological data analysis that have recently gained attention for their applications to RNA-seq data. Here, we assess the utility of supervised learning methods trained on RNA-seq data for a diverse range of biological classification tasks. We hypothesize that the transcript-level expression data are more informative for biological classification tasks than the gene-level expression data. Our large-scale assessment utilizes multiple data sets, organisms, lab groups, and RNA-seq analysis pipelines. Overall, we performed and assessed 61 biological classification problems that leverage three independent RNA-seq data sets and include over 2000 samples that come from multiple organisms, lab groups, and RNA-seq analyses. These 61 problems include predictions of the tissue type, sex, or age of the sample, healthy or cancerous phenotypes, and pathological tumor stages for the samples from the cancerous tissue. For each problem, the performance of three normalization techniques and six machine learning classifiers was explored. We find that for every single classification problem, the transcript-based classifiers outperform or are comparable with gene expression-based methods. The top-performing techniques reached a near perfect classification accuracy, demonstrating the utility of supervised learning for RNA-seq based data analysis.
Advanced LIGO's recent observations of gravitational waves (GWs) from merging binary black holes have opened up a unique laboratory to test general relativity (GR) in the highly relativistic regime. ...One of the tests used to establish the consistency of the first LIGO event with a binary black hole merger predicted by GR was the inspiral-merger-ringdown consistency test. This involves inferring the mass and spin of the remnant black hole from the inspiral (low-frequency) part of the observed signal and checking for the consistency of the inferred parameters with the same estimated from the post-inspiral (high-frequency) part of the signal. Based on the observed rate of binary black hole mergers, we expect the advanced GW observatories to observe hundreds of binary black hole mergers every year when operating at their design sensitivities, most of them with modest signal to noise ratios (SNRs). Anticipating such observations, this paper shows how constraints from a large number of events with modest SNRs can be combined to produce strong constraints on deviations from GR. Using kludge modified GR waveforms, we demonstrate how this test could identify certain types of deviations from GR if such deviations are present in the signal waveforms. We also study the robustness of this test against reasonable variations of a variety of different analysis parameters.
Weight loss remains the most common therapy advocated for reducing hepatic lipid in obesity and nonalcoholic fatty liver disease. Yet, reduction of body weight by lifestyle intervention is often ...modest, and thus, therapies which effectively modulate the burden of fatty liver but are not contingent upon weight loss are of the highest practical significance. However, the effect of aerobic exercise on liver fat independent of weight loss has not been clarified. We assessed the effect of aerobic exercise training on hepatic, blood, abdominal and muscle lipids in 19 sedentary obese men and women using magnetic resonance imaging and proton magnetic resonance spectroscopy (1H‐MRS). Four weeks of aerobic cycling exercise, in accordance with current physical activity guidelines, significantly reduced visceral adipose tissue volume by 12% (P < 0.01) and hepatic triglyceride concentration by 21% (P < 0.05). This was associated with a significant (14%) reduction in plasma free fatty acids (P < 0.05). Exercise training did not alter body weight, vastus lateralis intramyocellular triglyceride concentration, abdominal subcutaneous adipose tissue volume, 1H‐MRS–measured hepatic lipid saturation, or HOMA‐IR (homeostasis model assessment of insulin resistance; P > 0.05). Conclusion: These data provide the first direct experimental evidence demonstrating that regular aerobic exercise reduces hepatic lipids in obesity even in the absence of body weight reduction. Physical activity should be strongly promoted for the management of fatty liver, the benefits of which are not exclusively contingent upon weight loss. (HEPATOLOGY 2009.)
Background & Aims Aerobic exercise reduces liver fat and visceral adipose tissue (VAT). However, there is limited data from randomized trials to inform exercise programming recommendations. This ...study examined the efficacy of commonly prescribed exercise doses for reducing liver fat and VAT using a randomized placebo-controlled design. Methods Inactive and overweight/obese adults received 8 weeks of either; i) low to moderate intensity, high volume aerobic exercise (LO:HI, 50% VO2peak , 60 min, 4 d/week); ii) high intensity, low volume aerobic exercise (HI:LO, 70% VO2peak , 45 min, 3 d/week); iii) low to moderate intensity, low volume aerobic exercise (LO:LO, 50% VO2peak, 45 min, 3 d/week); or iv) placebo (PLA). Liver fat (spectroscopy) and VAT (magnetic resonance imaging) were measured before and after intervention. Results Forty-seven of the 48 (n = 12 in each group) participants completed the trial. There were no serious adverse events. There was a significant change in group × time interaction in liver fat, which reduced in HI:LO by 2.38 ± 0.73%, in LO:HI by 2.62 ± 1.00%, and in LO:LO by 0.84 ± 0.47% but not in PLA (increase of 1.10 ± 0.62%) ( p = 0.04). There was a significant reduction in VAT in HI:LO (−258.38 ± 87.78 cm3 ), in LO:HI (−386.80 ± 119.5 cm3 ), and in LO:LO (−212.96 ± 105.54 cm3 ), but not in PLA (92.64 ± 83.46 cm3 ) ( p = 0.03). There were no significant differences between the dose or intensity of the exercise regimen and reductions in liver fat or VAT ( p >0.05). Conclusion The study found no difference in efficacy of liver fat reduction by either aerobic exercise dose or intensity. All of the aerobic exercise regimens employed reduced liver fat and VAT by a small amount without clinically significant weight loss.
At the earliest stage of battery development, differential scanning calorimetry (DSC) of a sample with all battery cell stack materials can provide quantitative data on the reaction thermochemistry. ...The resulting quantitative thermochemical map of expected reactions upon heating can then guide chemistry and component development toward improved cell safety. In this work, we construct Li0.43CoO2 + C + PVDF|Li6.4La3Zr1.4Ta0.6O12|Li microcell DSC samples with capacity-matched electrodes and test to 500 °C. Notable observations are: (1) ∼74% of the O2 released from the Li0.43CoO2 cathode reacts with C to form CO2 rather than with molten Li to produce Li2O, (2) PVDF pyrolysis (>400 °C) releases HF gas that exothermically reacts with Li to form LiF, and (3) reactions involving oxygen (e.g., CO2 and Li2O formation) account for ∼60% of the total heat released, and reactions involving HF (e.g., LiF formation) account for ∼36% of the total heat released.
Cognitive impairments are a common consequence of traumatic brain injury (TBI). The hippocampus is a subcortical structure that plays a key role in the formation of declarative memories and is highly ...vulnerable to TBI. The α7 nicotinic acetylcholine receptor (nAChR) is highly expressed in the hippocampus and reduced expression and function of this receptor are linked with cognitive impairments in Alzheimer's disease and schizophrenia. Positive allosteric modulation of α7 nAChRs with AVL-3288 enhances receptor currents and improves cognitive functioning in naïve animals and healthy human subjects. Therefore, we hypothesized that targeting the α7 nAChR with the positive allosteric modulator AVL-3288 would enhance cognitive functioning in the chronic recovery period of TBI. To test this hypothesis, adult male Sprague Dawley rats received moderate parasagittal fluid-percussion brain injury or sham surgery. At 3 months after recovery, animals were treated with vehicle or AVL-3288 at 30 min prior to cue and contextual fear conditioning and the water maze task. Treatment of TBI animals with AVL-3288 rescued learning and memory deficits in water maze retention and working memory. AVL-3288 treatment also improved cue and contextual fear memory when tested at 24 hr and 1 month after training, when TBI animals were treated acutely just during fear conditioning at 3 months post-TBI. Hippocampal atrophy but not cortical atrophy was reduced with AVL-3288 treatment in the chronic recovery phase of TBI. AVL-3288 application to acute hippocampal slices from animals at 3 months after TBI rescued basal synaptic transmission deficits and long-term potentiation (LTP) in area CA1. Our results demonstrate that AVL-3288 improves hippocampal synaptic plasticity, and learning and memory performance after TBI in the chronic recovery period. Enhancing cholinergic transmission through positive allosteric modulation of the α7 nAChR may be a novel therapeutic to improve cognition after TBI.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As current gravitational wave (GW) detectors increase in sensitivity, and particularly as new instruments are being planned, there is the possibility that ground-based GW detectors will observe GWs ...from highly eccentric neutron star binaries. We present the first detailed study of highly eccentric BNS systems with full (3+1)D numerical relativity simulations using consistent initial conditions, i.e., setups which are in agreement with the Einstein equations and with the equations of general relativistic hydrodynamics in equilibrium. Overall, our simulations cover two different equations of state (EOSs), two different spin configurations, and three to four different initial eccentricities for each pairing of EOS and spin. We extract from the simulated waveforms the frequency of the f-mode oscillations induced during close encounters before the merger of the two stars. The extracted frequency is in good agreement with f-mode oscillations of individual stars for the irrotational cases, which allows an independent measure of the supranuclear equation of state not accessible for binaries on quasicircular orbits. The energy stored in these f-mode oscillations can be as large as 10−3 M⊙∼1051 erg, even with a soft EOS. In order to estimate the stored energy, we also examine the effects of mode mixing due to the stars’ offset from the origin on the f-mode contribution to the GW signal. While in general (eccentric) neutron star mergers produce bright electromagnetic counterparts, we find that for the considered cases with fixed initial separation the luminosity decreases when the eccentricity becomes too large, due to a decrease of the ejecta mass. Finally, the use of consistent initial configurations also allows us to produce high-quality waveforms for different eccentricities which can be used as a test bed for waveform model development of highly eccentric binary neutron star systems.
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