3,639 research outputs found
Statistics of Cycles: How Loopy is your Network?
We study the distribution of cycles of length h in large networks (of size
N>>1) and find it to be an excellent ergodic estimator, even in the extreme
inhomogeneous case of scale-free networks. The distribution is sharply peaked
around a characteristic cycle length, h* ~ N^a. Our results suggest that h* and
the exponent a might usefully characterize broad families of networks. In
addition to an exact counting of cycles in hierarchical nets, we present a
Monte-Carlo sampling algorithm for approximately locating h* and reliably
determining a. Our empirical results indicate that for small random scale-free
nets of degree exponent g, a=1/(g-1), and a grows as the nets become larger.Comment: Further work presented and conclusions revised, following referee
report
Nova-1 Regulates Neuron-Specific Alternative Splicing and Is Essential for Neuronal Viability
AbstractWe have combined genetic and biochemical approaches to analyze the function of the RNA-binding protein Nova-1, the paraneoplastic opsoclonus-myoclonus ataxia (POMA) antigen. Nova-1 null mice die postnatally from a motor deficit associated with apoptotic death of spinal and brainstem neurons. Nova-1 null mice show specific splicing defects in two inhibitory receptor pre-mRNAs, glycine α2 exon 3A (GlyRα2 E3A) and GABAA exon γ2L. Nova protein in brain extracts specifically bound to a previously identified GlyRα2 intronic (UCAUY)3 Nova target sequence, and Nova-1 acted directly on this element to increase E3A splicing in cotransfection assays. We conclude that Nova-1 binds RNA in a sequence-specific manner to regulate neuronal pre-mRNA alternative splicing; the defect in splicing in Nova-1 null mice provides a model for understanding the motor dysfunction in POMA
The impact of elbow and knee joint lesions on abnormal gait and posture of sows
<p>Abstract</p> <p>Background</p> <p>Joint lesions occur widespread in the Danish sow population and they are the most frequent cause for euthanasia. Clinically, it is generally impossible to differentiate between various types of non-inflammatory joint lesions. Consequently, it is often necessary to perform a post mortem examination in order to diagnose these lesions. A study was performed in order to examine the relation of abnormal gait and posture in sows with specific joint lesions, and thereby obtaining a clinical diagnostic tool, to be used by farmers and veterinarians for the evaluation of sows with joint problems.</p> <p>Methods</p> <p>The gait, posture and lesions in elbow- and knee joints of 60 randomly selected sows from one herd were scored clinically and pathologically. Associations between the scorings were estimated.</p> <p>Results</p> <p>The variables 'fore- and hind legs turned out' and 'stiff in front and rear' were associated with lesions in the elbow joint, and the variables 'hind legs turned out' and 'stiff in rear' were associated with lesions in the knee joint.</p> <p>Conclusion</p> <p>It was shown that specified gait and posture variables reflected certain joint lesions. However, further studies are needed to strengthen and optimize the diagnostic tool.</p
Increases in bioactive IGF do not parallel increases in total IGF-I during growth hormone treatment of children born SGA.
BACKGROUND: Some children born small for gestational age (SGA) experience supra-physiological insulin-like growth factor-I (IGF-I) concentrations during GH treatment. However, measurements of total IGF-I concentrations may not reflect the bioactive fraction of IGF-I which reaches the IGF-I receptor at target organs. We examined endogenous IGF-bioactivity using an IGF-I kinase receptor activation (KIRA) assay that measures the ability of IGF-I to activate the IGF-IR in vitro. AIM: To compare responses of bioactive IGF and total IGF-I concentrations in short GH treated SGA children in the North European Small for Gestational Age Study (NESGAS). RESULTS: Bioactive IGF increased with age in healthy pre-pubertal children (n=94). SGA children had low-normal bioactive IGF levels at baseline (-0.12 (1.8 SD), increasing significantly after one year of high-dose GH treatment to 1.1 (1.4) SD, p2SD (mean IGF-I 2.8 SDS), whereas only 15% (n=15) had levels of bioactive IGF slightly above normal reference values. At baseline, bioactive IGF (SDS) was significantly correlated to height (SDS) (r=0.29, p=0.005), in contrast to IGF-I (SDS) (r=0.17, p=0.10). IGF-I (SDS) was inversely correlated to delta height (SDS) after one year of high-dose GH treatment (r=-0.22, p=0.02). CONCLUSION: In contrast to total IGF-I concentrations, bioactive IGF stayed within the normal reference ranges for most SGA children during the first year of GH treatment
Calibration of myocardial T2 and T1 against iron concentration.
BACKGROUND: The assessment of myocardial iron using T2* cardiovascular magnetic resonance (CMR) has been validated and calibrated, and is in clinical use. However, there is very limited data assessing the relaxation parameters T1 and T2 for measurement of human myocardial iron.
METHODS: Twelve hearts were examined from transfusion-dependent patients: 11 with end-stage heart failure, either following death (n=7) or cardiac transplantation (n=4), and 1 heart from a patient who died from a stroke with no cardiac iron loading. Ex-vivo R1 and R2 measurements (R1=1/T1 and R2=1/T2) at 1.5 Tesla were compared with myocardial iron concentration measured using inductively coupled plasma atomic emission spectroscopy.
RESULTS: From a single myocardial slice in formalin which was repeatedly examined, a modest decrease in T2 was observed with time, from mean (± SD) 23.7 ± 0.93 ms at baseline (13 days after death and formalin fixation) to 18.5 ± 1.41 ms at day 566 (p<0.001). Raw T2 values were therefore adjusted to correct for this fall over time. Myocardial R2 was correlated with iron concentration [Fe] (R2 0.566, p<0.001), but the correlation was stronger between LnR2 and Ln[Fe] (R2 0.790, p<0.001). The relation was [Fe] = 5081•(T2)-2.22 between T2 (ms) and myocardial iron (mg/g dry weight). Analysis of T1 proved challenging with a dichotomous distribution of T1, with very short T1 (mean 72.3 ± 25.8 ms) that was independent of iron concentration in all hearts stored in formalin for greater than 12 months. In the remaining hearts stored for <10 weeks prior to scanning, LnR1 and iron concentration were correlated but with marked scatter (R2 0.517, p<0.001). A linear relationship was present between T1 and T2 in the hearts stored for a short period (R2 0.657, p<0.001).
CONCLUSION: Myocardial T2 correlates well with myocardial iron concentration, which raises the possibility that T2 may provide additive information to T2* for patients with myocardial siderosis. However, ex-vivo T1 measurements are less reliable due to the severe chemical effects of formalin on T1 shortening, and therefore T1 calibration may only be practical from in-vivo human studies
Genetic markers of insulin sensitivity and insulin secretion are associated with spontaneous postnatal growth and response to growth hormone treatment in short SGA children: the North European SGA Study (NESGAS).
PURPOSE: The wide heterogeneity in the early growth and metabolism of children born small for gestational age (SGA), both before and during GH therapy, may reflect common genetic variations related to insulin secretion or sensitivity. METHOD: Combined multiallele single nucleotide polymorphism scores with known associations with insulin sensitivity or insulin secretion were analyzed for their relationships with spontaneous postnatal growth and first-year responses to GH therapy in 96 short SGA children. RESULTS: The insulin sensitivity allele score (GS-InSens) was positively associated with spontaneous postnatal weight gain (regression coefficient [B]: 0.12 SD scores per allele; 95% confidence interval [CI], 0.01-0.23; P = .03) and also in response to GH therapy with first-year height velocity (B: 0.18 cm/y per allele; 95% CI, 0.02-0.35; P = .03) and change in IGF-1 (B: 0.17 SD scores per allele; 95% CI, 0.00-0.32; P = .03). The association with first-year height velocity was independent of reported predictors of response to GH therapy (adjusted P = .04). The insulin secretion allele score (GS-InSec) was positively associated with spontaneous postnatal height gain (B: 0.15; 95% CI, 0.01-0.30; P = .03) and disposition index both before (B: 0.02; 95% CI, 0.00-0.04; P = .04) and after 1 year of GH therapy (B: 0.03; 95% CI, 0.01-0.05; P = .002), but not with growth and IGF-1 responses to GH therapy. Neither of the allele scores was associated with size at birth. CONCLUSION: Genetic allele scores indicative of insulin sensitivity and insulin secretion were associated with spontaneous postnatal growth and responses to GH therapy in short SGA children. Further pharmacogenetic studies may support the rationale for adjuvant therapies by informing the mechanisms of treatment response.This study was funded by a research grant from The Danish Council for
Independent Research/ Medical Sciences and a research grant from Novo Nordisk A/S.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1210/jc.2014-3469
Discovering study-specific gene regulatory networks
This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets
Comments on the continuing widespread and unnecessary use of a defective emission equation in field emission related literature
Field electron emission (FE) has relevance in many different technological
contexts. However, many related technological papers use a physically defective
elementary FE equation for local emission current density (LECD). This equation
takes the tunneling barrier as exactly triangular, as in the original FE theory
of 90 years ago. More than 60 years ago, it was shown that the so-called
Schottky-Nordheim (SN) barrier, which includes an image-potential-energy term
(that models exchange-and-correlation effects) is better physics. For a
metal-like emitter with work-function 4.5 eV, the SN-barrier-related
Murphy-Good FE equation predicts LECD values that are higher than the
elementary equation values by a large factor, often between around 250 and
around 500. By failing to mention/apply this 60-year-old established science,
or to inform readers of the large errors associated with the elementary
equation, many papers (aided by defective reviewing) spread a new kind of
"pathological science", and create a modern research-integrity problem. The
present paper aims to enhance author and reviewer awareness by summarizing
relevant aspects of FE theory, by explicitly identifying the misjudgment in the
original 1928 Fowler-Nordheim paper, by explicitly calculating the size of the
resulting error, and by showing in detail why most FE theoreticians regard the
1950s modifications as better physics. Suggestions are made, about nomenclature
and about citation practice, that may help to diminish misunderstandings.Comment: Submitted for publication; in v2 a correction to historical
information (with no numerical consequences) has been made in Appendix
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