Comparing Executive Functions in Dancers Versus Aerobic Exercisers: A Study on Older Adults

Many older adults may experience cognitive decline with aging, and with a rising aging population it is important to investigate interventions that improve cognitive functions. The purpose of this study was to assess differences in executive functioning between older adult dancers and older adult aerobic exercisers. Given that dance involves the use of executive functions, in addition to engaging in aerobic exercise, older adult dancers were expected to score higher on the executive functioning tasks than the older adult aerobic exercisers. Using the Cambridge Brain Sciences Battery to assess executive functioning, this study sought to compare older adults, 50 years old and above, with 10 or more years of experience in dance or aerobic exercise and a control group with less than or equal to 1 year of experience in these activities. Because no participants were available for the aerobic exercise group, the study simply compared two older adult dancers with six older adults in the control group. A one-way between-groups analysis of variance indicated that the dance group and the control group did not differ significantly on any executive function measures. Specifically, the dance group and the control group did not differ in inhibitory control, planning, or working memory. However, these findings need to be interpreted with caution as the low sample size in both groups resulted in the study to be underpowered. Therefore, it cannot be definitively concluded that dance is not associated with higher cognitive functioning compared to the control group or the aerobic exercise group

A Caching Scheme to Accelerate Kinetic Monte Carlo Simulations of Catalytic Reactions

Kinetic Monte Carlo (KMC) simulations have been instrumental in advancing our fundamental understanding of heterogeneously catalyzed reactions, with particular emphasis on structure sensitivity, ensemble effects, and the interplay between adlayer structure and adsorbate-adsorbate lateral interactions in shaping the observed kinetics. Yet, the computational cost of KMC remains high, thereby motivating the development of acceleration schemes that would improve the simulation effciency. We present an exact such scheme, which implements a caching algorithm along with shared-memory parallelization to improve the computational performance of simulations incorporating long-range adsorbate-adsorbate lateral interactions. This scheme is based on caching information about the energetic interaction patterns associated with the products of each possible lattice process (adsorption, desorption, reaction etc). Thus, every time a reaction occurs ("ongoing reaction") it enables fast updates of the rate constants of "affected reactions", i.e. possible reactions in the region of influence of the "ongoing reaction". Benchmarks on KMC simulations of NOx oxidation/reduction, yield acceleration factors of up to 20× when comparing single-thread runs without caching to runs on 16 threads with caching, for simulations with a cluster expansion Hamiltonian that incorporates up to 8th nearest-neighbor interactions

Coupling the time-warp algorithm with the graph-theoretical kinetic Monte Carlo framework for distributed simulations of heterogeneous catalysts

Despite the successful and ever widening adoption of kinetic Monte Carlo (KMC) simulations in the area of surface science and heterogeneous catalysis, the accessible length scales are still limited by the inherently sequential nature of the KMC framework. Simulating long-range surface phenomena, such as catalytic reconstruction and pattern formation, requires consideration of large surfaces/lattices, at the μm scale and beyond. However, handling such lattices with the sequential KMC framework is extremely challenging due to the heavy memory footprint and computational demand. The Time-Warp algorithm proposed by Jefferson [ACM. Trans. Program. Lang. Syst., 1985. 7: 404-425] offers a way to enable distributed parallelization of discrete event simulations. Thus, to enable high-fidelity simulations of challenging systems in heterogeneous catalysis, we have coupled the Time-Warp algorithm with the Graph-Theoretical KMC framework [J. Chem. Phys., 134(21): 214115; J. Chem. Phys., 139(22): 224706] and implemented the approach in the general-purpose KMC code Zacros. We have further developed a “parallel-emulation” serial algorithm, which produces identical results to those obtained from the distributed runs (with the Time-Warp algorithm) thereby validating the correctness of our implementation. These advancements make Zacros the first-of-its-kind general-purpose KMC code with distributed computing capabilities, thereby opening up opportunities for detailed meso-scale studies of heterogeneous catalysts and closer-than-ever comparisons of theory with experiments

From logical forms to SPARQL query with GETARUNS

We present a system for Question Answering which computes a prospective answer from Logical Forms produced by a full-fledged NLP for text understanding, and then maps the result onto schemata in SPARQL to be used for accessing the Semantic Web. As an intermediate step, and whenever there are complex concepts to be mapped, the system looks for a corresponding amalgam in YAGO classes. It is just by the internal structure of the Logical Form that we are able to produce a suitable and meaningful context for concept disambiguation. Logical Forms are the final output of a complex system for text understanding - GETARUNS - which can deal with different levels of syntactic and semantic ambiguity in the generation of a final structure, by accessing computational lexical equipped with sub-categorization frames and appropriate selectional restrictions applied to the attachment of complements and adjuncts. The system also produces pronominal binding and instantiates the implicit arguments, if needed, in order to complete the required Predicate Argument structure which is licensed by the semantic component

Modelling adsorption using an augmented two-dimensional statistical associating fluid theory: 2D-SAFT-VR Mie

We present an extension of the SAFT-VR Mie approach to model adsorption of molecular fluids based on a two-dimensional (2D) approximation to describe the adsorbed fluid. Analytical results are provided for the first- and second-order perturbation terms of the free energy for the 2D system. The adsorption model is based on the assumption that the particle pair interactions in the adsorbed and bulk phases are described with the same Mie potential exponents λa and λr, in contrast with the square-well version of the 2D-SAFT-VR approach in which it is considered necessary to modify the attractive ranges of the SW interactions. This important difference between the two approaches leads to a reduction in the number of molecular parameters to be determined. In order to demonstrate the performance of the 2D-SAFT-VR Mie approach, we present results for the the modelling of carbon dioxide (CO2) and methane (CH4) adsorbed onto dry coal

Human C-reactive protein aggravates osteoarthritis development in mice on a high-fat diet

Objective: C-reactive protein (CRP) levels can be elevated in osteoarthritis (OA) patients. In addition to indicating systemic inflammation, it is suggested that CRP itself can play a role in OA development. Obesity and metabolic syndrome are important risk factors for OA and also induce elevated CRP levels. Here we evaluated in a human CRP (hCRP)-transgenic mouse model whether CRP itself contributes to the development of ‘metabolic’ OA.Design: Metabolic OA was induced by feeding 12-week-old hCRP-transgenic males (hCRP-tg, n = 30) and wild-type littermates (n = 15) a 45 kcal% high-fat diet (HFD) for 38 weeks. Cartilage degradation, osteophytes and synovitis were graded on Safranin O-stained histological knee joint sections. Inflammatory status was assessed by plasma lipid profiling, flow cytometric analyses of blood immune cell populations and immunohistochemical staining of synovial macrophage subsets.Results: Male hCRP-tg mice showed aggravated OA severity and increased osteophytosis compared with their wild-type littermates. Both classical and non-classical monocytes showed increased expression of CCR2 and CD86 in hCRP-tg males. HFD-induced effects were evident for nearly all lipids measured and indicated a similar low-grade systemic inflammation for both genotypes. Synovitis scores and synovial macrophage subsets were similar in the two groups.Conclusions: Human CRP expression in a background of HFD-induced metabolic dysfunction resulted in the aggravation of OA through increased cartilage degeneration and osteophytosis. Increased recruitment of classical and non-classical monocytes might be a mechanism of action through which CRP is involved in aggravating this process. These findings suggest interventions selectively directed against CRP activity could ameliorate metabolic OA development

Re-calculating the cost of coccidiosis in chickens

Coccidiosis, caused by Eimeria species parasites, has long been recognised as an economically significant disease of chickens. As the global chicken population continues to grow, and its contribution to food security intensifies, it is increasingly important to assess the impact of diseases that compromise chicken productivity and welfare. In 1999, Williams published one of the most comprehensive estimates for the cost of coccidiosis in chickens, featuring a compartmentalised model for the costs of prophylaxis, treatment and losses, indicating a total cost in excess of £38 million in the United Kingdom (UK) in 1995. In the 25 years since this analysis the global chicken population has doubled and systems of chicken meat and egg production have advanced through improved nutrition, husbandry and selective breeding of chickens, and wider use of anticoccidial vaccines. Using data from industry representatives including veterinarians, farmers, production and health experts, we have updated the Williams model and estimate that coccidiosis in chickens cost the UK £99.2 million in 2016 (range £73.0–£125.5 million). Applying the model to data from Brazil, Egypt, Guatemala, India, New Zealand, Nigeria and the United States resulted in estimates that, when extrapolated by geographical region, indicate a global cost of ~ £10.4 billion at 2016 prices (£7.7–£13.0 billion), equivalent to £0.16/chicken produced. Understanding the economic costs of livestock diseases can be advantageous, providing baselines to evaluate the impact of different husbandry systems and interventions. The updated cost of coccidiosis in chickens will inform debates on the value of chemoprophylaxis and development of novel anticoccidial vaccines

Transcriptional analysis of adipose tissue during development reveals depot-specific responsiveness to maternal dietary supplementation

Brown adipose tissue (BAT) undergoes pronounced changes after birth coincident with the loss of the BAT-specifc uncoupling protein (UCP)1 and rapid fat growth. The extent to which this adaptation may vary between anatomical locations remains unknown, or whether the process is sensitive to maternal dietary supplementation. We, therefore, conducted a data mining based study on the major fat depots (i.e. epicardial, perirenal, sternal (which possess UCP1 at 7 days), subcutaneous and omental) (that do not possess UCP1) of young sheep during the frst month of life. Initially we determined what effect adding 3% canola oil to the maternal diet has on mitochondrial protein abundance in those depots which possessed UCP1. This demonstrated that maternal dietary supplementation delayed the loss of mitochondrial proteins, with the amount of cytochrome C actually being increased. Using machine learning algorithms followed by weighted gene co-expression network analysis, we demonstrated that each depot could be segregated into a unique and concise set of modules containing co-expressed genes involved in adipose function. Finally using lipidomic analysis following the maternal dietary intervention, we confrmed the perirenal depot to be most responsive. These insights point at new research avenues for examining interventions to modulate fat development in early life

In vitro inhibitory activities of selected Australian medicinal plant extracts against protein glycation, angiotensin converting enzyme (ACE) and digestive enzymes linked to type II diabetes

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background There is a need to develop potential new therapies for the management of diabetes and hypertension. Australian medicinal plants collected from the Kuuku I’yu (Northern Kaanju) homelands, Cape York Peninsula, Queensland, Australia were investigated to determine their therapeutic potential. Extracts were tested for inhibition of protein glycation and key enzymes relevant to the management of hyperglycaemia and hypertension. The inhibitory activities were further correlated with the antioxidant activities. Methods Extracts of five selected plant species were investigated: Petalostigma pubescens, Petalostigma banksii, Memecylon pauciflorum, Millettia pinnata and Grewia mesomischa. Enzyme inhibitory activity of the plant extracts was assessed against α-amylase, α-glucosidase and angiotensin converting enzyme (ACE). Antiglycation activity was determined using glucose-induced protein glycation models and formation of protein-bound fluorescent advanced glycation endproducts (AGEs). Antioxidant activity was determined by measuring the scavenging effect of plant extracts against 1, 1-diphenyl-2-picryl hydrazyl (DPPH) and using the ferric reducing anti-oxidant potential assay (FRAP). Total phenolic and flavonoid contents were also determined. Results Extracts of the leaves of Petalostigma banksii and P. pubescens showed the strongest inhibition of α-amylase with IC50 values of 166.50 ± 5.50 μg/mL and 160.20 ± 27.92 μg/mL, respectively. The P. pubescens leaf extract was also the strongest inhibitor of α-glucosidase with an IC50 of 167.83 ± 23.82 μg/mL. Testing for the antiglycation potential of the extracts, measured as inhibition of formation of protein-bound fluorescent AGEs, showed that P. banksii root and fruit extracts had IC50 values of 34.49 ± 4.31 μg/mL and 47.72 ± 1.65 μg/mL, respectively, which were significantly lower (p < 0.05) than other extracts. The inhibitory effect on α-amylase, α-glucosidase and the antiglycation potential of the extracts did not correlate with the total phenolic, total flavonoid, FRAP or DPPH. For ACE inhibition, IC50 values ranged between 266.27 ± 6.91 to 695.17 ± 15.38 μg/mL. Conclusions The tested Australian medicinal plant extracts inhibit glucose-induced fluorescent AGEs, α-amylase, α-glucosidase and ACE with extracts of Petalostigma species showing the most promising activity. These medicinal plants could potentially be further developed as therapeutic agents in the treatment of hyperglycaemia and hypertension

Plasma lipid biomarker signatures in squamous carcinoma and adenocarcinoma lung cancer patients

There is a clinical need for reliable biomarkers for lung cancer that permit early diagnosis of the disease and provide prediction of histological phenotype. A prospective study design was used with a study population of patients with suspected lung cancer. Blood samples were collected from 17 patients with histologically confirmed squamous cell lung carcinoma, 17 individuals with adenocarcinoma, and 17 control individuals who did not subsequently have a diagnosis of lung cancer or any other cancer. Blood plasma samples were analysed for their lipid profiles using liquid chromatography coupled with high resolution mass spectrometry. Data were analysed using multivariate statistical methods. There was good separation between histological subtypes and control groups and also between individuals with a subsequent diagnosis of adenocarcinoma and squamous cell carcinoma (sensitivity 80 %, specificity 83 %, Q2 = 0.70). Alterations in the levels of different classes of lipids including triglycerides (TGs), phosphatidylinositols (PIs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), free fatty acids, lysophospholipids and sphingolipids were observed in squamous carcinoma and adenocarcinoma lung cancer patients when compared with control patients. In conclusion, this study has identified candidate lipid biomarkers of non-small cell lung cancer patients which may be helpful to indicate the tumour subtype and to differentiate them from patients who do not have lung cancer. Measuring these biomarkers has the potential to improve diagnosis in patients with suspected lung cancer and risk stratification in screening