601 research outputs found
Modeling and verifying a broad array of network properties
Motivated by widely observed examples in nature, society and software, where
groups of already related nodes arrive together and attach to an existing
network, we consider network growth via sequential attachment of linked node
groups, or graphlets. We analyze the simplest case, attachment of the three
node V-graphlet, where, with probability alpha, we attach a peripheral node of
the graphlet, and with probability (1-alpha), we attach the central node. Our
analytical results and simulations show that tuning alpha produces a wide range
in degree distribution and degree assortativity, achieving assortativity values
that capture a diverse set of many real-world systems. We introduce a
fifteen-dimensional attribute vector derived from seven well-known network
properties, which enables comprehensive comparison between any two networks.
Principal Component Analysis (PCA) of this attribute vector space shows a
significantly larger coverage potential of real-world network properties by a
simple extension of the above model when compared against a classic model of
network growth.Comment: To appear in Europhysics Letter
Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.
Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis
Visualizing dimensionality reduction of systems biology data
One of the challenges in analyzing high-dimensional expression data is the
detection of important biological signals. A common approach is to apply a
dimension reduction method, such as principal component analysis. Typically,
after application of such a method the data is projected and visualized in the
new coordinate system, using scatter plots or profile plots. These methods
provide good results if the data have certain properties which become visible
in the new coordinate system and which were hard to detect in the original
coordinate system. Often however, the application of only one method does not
suffice to capture all important signals. Therefore several methods addressing
different aspects of the data need to be applied. We have developed a framework
for linear and non-linear dimension reduction methods within our visual
analytics pipeline SpRay. This includes measures that assist the interpretation
of the factorization result. Different visualizations of these measures can be
combined with functional annotations that support the interpretation of the
results. We show an application to high-resolution time series microarray data
in the antibiotic-producing organism Streptomyces coelicolor as well as to
microarray data measuring expression of cells with normal karyotype and cells
with trisomies of human chromosomes 13 and 21
A Geometric Variational Approach to Bayesian Inference
We propose a novel Riemannian geometric framework for variational inference
in Bayesian models based on the nonparametric Fisher-Rao metric on the manifold
of probability density functions. Under the square-root density representation,
the manifold can be identified with the positive orthant of the unit
hypersphere in L2, and the Fisher-Rao metric reduces to the standard L2 metric.
Exploiting such a Riemannian structure, we formulate the task of approximating
the posterior distribution as a variational problem on the hypersphere based on
the alpha-divergence. This provides a tighter lower bound on the marginal
distribution when compared to, and a corresponding upper bound unavailable
with, approaches based on the Kullback-Leibler divergence. We propose a novel
gradient-based algorithm for the variational problem based on Frechet
derivative operators motivated by the geometry of the Hilbert sphere, and
examine its properties. Through simulations and real-data applications, we
demonstrate the utility of the proposed geometric framework and algorithm on
several Bayesian models
HIPK2 and extrachromosomal histone H2B are separately recruited by Aurora-B for cytokinesis
Cytokinesis, the final phase of cell division, is necessary to form two distinct daughter cells with correct distribution of genomic and cytoplasmic materials. Its failure provokes genetically unstable states, such as tetraploidization and polyploidization, which can contribute to tumorigenesis. Aurora-B kinase controls multiple cytokinetic events, from chromosome condensation to abscission when the midbody is severed. We have previously shown that HIPK2, a kinase involved in DNA damage response and development, localizes at the midbody and contributes to abscission by phosphorylating extrachromosomal histone H2B at Ser14. Of relevance, HIPK2-defective cells do not phosphorylate H2B and do not successfully complete cytokinesis leading to accumulation of binucleated cells, chromosomal instability, and increased tumorigenicity. However, how HIPK2 and H2B are recruited to the midbody during cytokinesis is still unknown. Here, we show that regardless of their direct (H2B) and indirect (HIPK2) binding of chromosomal DNA, both H2B and HIPK2 localize at the midbody independently of nucleic acids. Instead, by using mitotic kinase-specific inhibitors in a spatio-temporal regulated manner, we found that Aurora-B kinase activity is required to recruit both HIPK2 and H2B to the midbody. Molecular characterization showed that Aurora-B directly binds and phosphorylates H2B at Ser32 while indirectly recruits HIPK2 through the central spindle components MgcRacGAP and PRC1. Thus, among different cytokinetic functions, Aurora-B separately recruits HIPK2 and H2B to the midbody and these activities contribute to faithful cytokinesis
Effects of a brief mindfulness-based intervention on emotional regulation and levels of mindfulness in senior students
Mindfulness-based interventions have been applied in diverse populations and achieved mental health benefits. This study examined the effects of a brief mindfulness program for emotional regulation and levels of mindfulness on senior students in Brazil. The intervention consisted of six weekly meetings attended by 30 participants. It is a pre-experimental research, with pre- and post-test comparative and correlation measurements. The preliminary results, which relied on parametrical and non-parametrical tests, revealed a reduction in total emotional regulation difficulties (p = 0.0001; r = − 0.55). Also, there was an increase in the levels of mindfulness in the subtests for both dimensions under evaluation: “Awareness” (p = 0.0001; d = 0.77) and “Acceptance” (p = 0.048; d = 0.37). By associating the amount of meditative practices performed by students with the variables, a significant positive correlation was found with the mindfulness dimension “Awareness” (rP = 0.422; p = 0.020), and there was a significant negative correlation with Difficulties in emotion regulation (rS = − 0.478; p = 0.008) and with its respective subscales “Non-acceptance” (rS = − 0.654; p = 0.0001) and “Clarity” (rS = − 0.463; p = 0.010). In conclusion, the application of a brief mindfulness-based intervention is promising in Brazilian university contexts; moreover, it can bring benefits to students, e.g., an increase in emotion regulation as well as in levels of mindfulness. We suggest that further research should use an experimental design and follow-up.info:eu-repo/semantics/publishedVersio
Statistical signatures of critical behavior in small systems
The cluster distributions of different systems are examined to search for
signatures of a continuous phase transition. In a system known to possess such
a phase transition, both sensitive and insensitive signatures are present;
while in systems known not to possess such a phase transition, only insensitive
signatures are present. It is shown that nuclear multifragmentation results in
cluster distributions belonging to the former category, suggesting that the
fragments are the result of a continuous phase transition.Comment: 31 pages, two columns with 30 figure
Renormalized couplings and scaling correction amplitudes in the N-vector spin models on the sc and the bcc lattices
For the classical N-vector model, with arbitrary N, we have computed through
order \beta^{17} the high temperature expansions of the second field derivative
of the susceptibility \chi_4(N,\beta) on the simple cubic and on the body
centered cubic lattices. (The N-vector model is also known as the O(N)
symmetric classical spin Heisenberg model or, in quantum field theory, as the
lattice
O(N) nonlinear sigma model.) By analyzing the expansion of \chi_4(N,\beta) on
the two lattices, and by carefully allowing for the corrections to scaling, we
obtain updated estimates of the critical parameters and more accurate tests of
the hyperscaling relation d\nu(N) +\gamma(N) -2\Delta_4(N)=0 for a range of
values of the spin dimensionality N, including
N=0 [the self-avoiding walk model], N=1 [the Ising spin 1/2 model],
N=2 [the XY model], N=3 [the classical Heisenberg model]. Using the recently
extended series for the susceptibility and for the second correlation moment,
we also compute the dimensionless renormalized four point coupling constants
and some universal ratios of scaling correction amplitudes in fair agreement
with recent renormalization group estimates.Comment: 23 pages, latex, no figure
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