STATISTICAL MEDIA OPTIMIZATION FOR LUTEIN PRODUCTION FROM MICROALGAE Auxenochlorella protothecoides SAG 211-7A

In this study, the heterotrophic production potential of the secondary carotenoid lutein by the green microalgae Auxenochlorella protothecoides SAG 211-7a was investigated. A sequential statistical technique was applied to optimize modified bold’s basal media (MBB) to enhance the lutein production from microalgae Auxenochlorella protothecoides SAG 211-7a. Taguchi orthogonal array method was applied to select the various independent variables which affect the lutein production. It showed that sucrose, yeast extract, MgSO4.7H2O and EDTA were the significant factors affect the lutein production. Further, to increase the lutein yield and to study the interaction between these factors response surface methodology (RSM) was employed. The statistical model was validated with respect to lutein production under the conditions predicted by the model containing sucrose 14.0 g/l, yeast extract 3.0 g/l, MgSO4.7H2O 0.8 g/l and EDTA 0.76 g/l. The production of lutein obtained experimentally using the above medium was 1303 ± 25.32 μg/l, which is in correlation with the predicted value of 1337.21 g/l by the RSM regression study. Thus after sequential statistical media optimization strategy a 5-fold enhancement in lutein production was achieved

Social gradients in self-reported health and well-being among adults aged 50 and over in Pune District, India

Background: India’s older population is projected to increase up to 96 million by 2011 with older people accounting for 18% of its population by 2051. The Study on Global Ageing and Adult Health aims to improve empirical understanding of health and well-being of older adults in developing countries. Objectives: To examine age and socio-economic changes on a range of key domains in self-reported health and well-being amongst older adults. Design: A cross-sectional survey of 5,430 adults aged 50 and over using a shortened version of the SAGE questionnaire to assess self-reported assessments (scales of 1–5) of performance, function, disability, quality of life and well-being. Self-reported responses were calibrated using anchoring vignettes in eight key domains of mobility, self-care, pain, cognition, interpersonal relationships, sleep/energy, affect, and vision. WHO Disability Assessment Schedule Index and WHO health scores were calculated to examine for associations with socio-demographic variables. Results: Disability in all domains increased with increasing age and decreasing levels of education. Females and the oldest old without a living spouse reported poorer health status and greater disability across all domains. Performance and functionality self-reports were similar across all SES quintiles. Self-reports on quality of life were not significantly influenced by socio-demographic variables. Discussion: The study provides standardised and comparable self-rated health data using anchoring vignettes in an older population. Though expectations of good health, function and performance decrease with age, self-reports of disability severity significantly increased with age, more so if female, if uneducated and living without a spouse. However, the presence or absence of spouse did not significantly alter quality of life self-reports, suggesting a possible protective effect provided by traditional joint family structures in India, where older people are social if not financial assets for their children

A frequentist framework of inductive reasoning

Reacting against the limitation of statistics to decision procedures, R. A. Fisher proposed for inductive reasoning the use of the fiducial distribution, a parameter-space distribution of epistemological probability transferred directly from limiting relative frequencies rather than computed according to the Bayes update rule. The proposal is developed as follows using the confidence measure of a scalar parameter of interest. (With the restriction to one-dimensional parameter space, a confidence measure is essentially a fiducial probability distribution free of complications involving ancillary statistics.) A betting game establishes a sense in which confidence measures are the only reliable inferential probability distributions. The equality between the probabilities encoded in a confidence measure and the coverage rates of the corresponding confidence intervals ensures that the measure's rule for assigning confidence levels to hypotheses is uniquely minimax in the game. Although a confidence measure can be computed without any prior distribution, previous knowledge can be incorporated into confidence-based reasoning. To adjust a p-value or confidence interval for prior information, the confidence measure from the observed data can be combined with one or more independent confidence measures representing previous agent opinion. (The former confidence measure may correspond to a posterior distribution with frequentist matching of coverage probabilities.) The representation of subjective knowledge in terms of confidence measures rather than prior probability distributions preserves approximate frequentist validity.Comment: major revisio

Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning

BACKGROUND: Neural substrates underlying motor learning have been widely investigated with neuroimaging technologies. Investigations have illustrated the critical regions of motor learning and further revealed parallel alterations of functional activation during imagination and execution after learning. However, little is known about the functional connectivity associated with motor learning, especially motor imagery learning, although benefits from functional connectivity analysis attract more attention to the related explorations. We explored whether motor imagery (MI) and motor execution (ME) shared parallel alterations of functional connectivity after MI learning. METHODOLOGY/PRINCIPAL FINDINGS: Graph theory analysis, which is widely used in functional connectivity exploration, was performed on the functional magnetic resonance imaging (fMRI) data of MI and ME tasks before and after 14 days of consecutive MI learning. The control group had no learning. Two measures, connectivity degree and interregional connectivity, were calculated and further assessed at a statistical level. Two interesting results were obtained: (1) The connectivity degree of the right posterior parietal lobe decreased in both MI and ME tasks after MI learning in the experimental group; (2) The parallel alterations of interregional connectivity related to the right posterior parietal lobe occurred in the supplementary motor area for both tasks. CONCLUSIONS/SIGNIFICANCE: These computational results may provide the following insights: (1) The establishment of motor schema through MI learning may induce the significant decrease of connectivity degree in the posterior parietal lobe; (2) The decreased interregional connectivity between the supplementary motor area and the right posterior parietal lobe in post-test implicates the dissociation between motor learning and task performing. These findings and explanations further revealed the neural substrates underpinning MI learning and supported that the potential value of MI learning in motor function rehabilitation and motor skill learning deserves more attention and further investigation

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs

Myocardial energy depletion and dynamic systolic dysfunction in hypertrophic cardiomyopathy

Evidence indicates that anatomical and physiological phenotypes of hypertrophic cardiomyopathy (HCM) stem from genetically mediated, inefficient cardiomyocyte energy utilization, and subsequent cellular energy depletion. However, HCM often presents clinically with normal left ventricular (LV) systolic function or hyperkinesia. If energy inefficiency is a feature of HCM, why is it not manifest as resting LV systolic dysfunction? In this Perspectives article, we focus on an idiosyncratic form of reversible systolic dysfunction provoked by LV obstruction that we have previously termed the 'lobster claw abnormality' — a mid-systolic drop in LV Doppler ejection velocities. In obstructive HCM, this drop explains the mid-systolic closure of the aortic valve, the bifid aortic pressure trace, and why patients cannot increase stroke volume with exercise. This phenomenon is characteristic of a broader phenomenon in HCM that we have termed dynamic systolic dysfunction. It underlies the development of apical aneurysms, and rare occurrence of cardiogenic shock after obstruction. We posit that dynamic systolic dysfunction is a manifestation of inefficient cardiomyocyte energy utilization. Systolic dysfunction is clinically inapparent at rest; however, it becomes overt through the mechanism of afterload mismatch when LV outflow obstruction is imposed. Energetic insufficiency is also present in nonobstructive HCM. This paradigm might suggest novel therapies. Other pathways that might be central to HCM, such as myofilament Ca2+ hypersensitivity, and enhanced late Na+ current, are discussed

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

Systems microscopy approaches to understand cancer cell migration and metastasis

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration