DNA methylation is implicated in a surprising diversity of regulatory, evolutionary processes and diseases in eukaryotes. The introduction of whole-genome bisulfite sequencing has enabled the study ...of DNA methylation at a single-base resolution, revealing many new aspects of DNA methylation and highlighting the usefulness of methylome data in understanding a variety of genomic phenomena. As the number of publicly available whole-genome bisulfite sequencing studies reaches into the hundreds, reliable and convenient tools for comparing and analyzing methylomes become increasingly important. We present MethPipe, a pipeline for both low and high-level methylome analysis, and MethBase, an accompanying database of annotated methylomes from the public domain. Together these resources enable researchers to extract interesting features from methylomes and compare them with those identified in public methylomes in our database.
Abstract
We identify cosmic voids from galaxy density fields under the theory of void–cluster correspondence. We extend the previous novel void-identification method developed for the matter density ...field to the galaxy density field for practical applications. From cosmological
N
-body simulations, we construct galaxy number- and mass-weighted density fields to identify cosmic voids that are counterparts of galaxy clusters of a specific mass. The parameters for the cluster-counterpart void identification such as Gaussian smoothing scale, density threshold, and core volume fraction are found for galaxy density fields. We achieve about 60%–67% of completeness and reliability for identifying the voids of corresponding cluster mass above 3 × 10
14
h
−1
M
⊙
from a galaxy sample with the mean number density,
n
¯
=
4.4
×
10
−
3
(
h
−
1
Mpc
)
−
3
. When the mean density is increased to
n
¯
=
10
−
2
(
h
−
1
Mpc
)
−
3
, the detection rate is enhanced by ∼2%–7% depending on the
mass scale
of voids. We find that the detectability is insensitive to the density weighting scheme applied to generate the density field. Our result demonstrates that we can apply this method to the galaxy redshift survey data to identify cosmic voids corresponding statistically to the galaxy clusters in a given mass range.
Abstract
The apparent shape of galaxy clustering depends on the adopted cosmology used to convert observed redshift to comoving distance, the
r
(
z
) relation, as it changes the line elements along ...and across the line of sight differently. The Alcock–Paczyński (AP) test exploits this property to constrain the expansion history of the universe. We present an extensive review of past studies on the AP test. We adopt an extended AP test method introduced by Park et al., which uses the full shape of redshift-space two-point correlation function (CF) as the standard shape, and apply it to the Sloan Digital Sky Survey DR7, BOSS, and eBOSS LRG samples covering the redshift range up to
z
= 0.8. We calibrate the test against the nonlinear cosmology-dependent systematic evolution of the CF shape using Multiverse simulations. We focus on examining whether or not the flat Lambda cold dark matter (ΛCDM)
concordance
model is consistent with observation. We constrain the flat
w
CDM model to have
w
=
−
0.892
−
0.050
+
0.045
and
Ω
m
=
0.282
−
0.023
+
0.024
from our AP test alone, which is significantly tighter than the constraints from the BAO or SNe Ia methods by a factor of 3–6. When the AP test result is combined with the recent BAO and SNe Ia results, we obtain
w
=
−
0.903
−
0.023
+
0.023
and
Ω
m
=
0.285
−
0.009
+
0.014
. This puts a strong tension with the flat ΛCDM model with
w
= −1 at the 4.2
σ
level. Consistency with
w
= −1 is obtained only when the Planck cosmic microwave background (CMB) observation is combined. It remains to be seen whether this tension between observations of galaxy distribution at low redshifts and CMB anisotropy at the decoupling epoch becomes greater in future studies and leads us to a new paradigm of cosmology.
Receptor for advanced glycation end products (RAGE) plays a role in inflammatory reactions. The soluble form of RAGE (sRAGE) acts as a decoy to inhibit interactions of RAGE with advanced glycation ...end products such as High mobility group box 1 (HMGB1). We have demonstrated that HMGB1 directs Th17 skewing by regulating dendritic cell (DC) functions in a previous study. However, the protective effects of HMGB1 blockade with sRAGE in the development of neutrophilic asthma remain unclear. Here, we showed that allergen challenge decreased expression of sRAGE in a murine model of neutrophilic asthma, correlating well with neutrophil counts and interleukin (IL)-17 production. When HMGB1 signalling was blocked by intratracheal administration of sRAGE before sensitisation, HMGB1 expression, neutrophilic inflammation, and Th17-type responses were reduced significantly. Anti-asthma effects of sRAGE were achieved by inhibition of RAGE and IL-23 expression in airway CD11c
antigen-presenting cells. Finally, we showed that sRAGE inhibited Th17 polarisation induced by recombinant HMGB1 (rHMGB1)-activated dendritic cells (DCs) in vitro. Adoptive transfer of rHMGB1-activated DCs was sufficient to restore airway inflammation, whereas transfer of rHMGB1 plus sRAGE-activated DCs significantly reduced neutrophilic inflammation. Thus, sRAGE prevents Th17-mediated airway inflammation in neutrophilic asthma at least partly by blocking HMGB1/RAGE signalling in DCs.
We present measurements of the two-dimensional genus of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) catalogs to constrain cosmological parameters governing the shape of the matter ...power spectrum. The BOSS data are divided into 12 concentric shells over the redshift range 0.2 < z < 0.6, and we extract the genus from the projected two-dimensional galaxy density fields. We compare the genus amplitudes to their Gaussian expectation values, exploiting the fact that this quantity is relatively insensitive to nonlinear gravitational collapse. The genus amplitude provides a measure of the shape of the linear matter power spectrum and is principally sensitive to ch2 and scalar spectral index ns. A strong negative degeneracy between ch2 and ns is observed, as both can increase small-scale power by shifting the peak and tilting the power spectrum, respectively. We place a constraint on the particular combination -we find after combining the LOWZ and CMASS data sets, assuming a flat ΛCDM cosmology. This result is practically insensitive to reasonable variations of the power spectrum amplitude and linear galaxy bias. Our results are consistent with the Planck best fit .
The outskirts of galaxy clusters are continuously disturbed by mergers and gas infall along filaments, which in turn induce turbulent flow motions and shock waves. We examine the properties of shocks ...that form within r sub(200) in sample galaxy clusters from structure formation simulations. While most of these shocks are weak and inefficient accelerators of cosmic rays (CRs), there are a number of strong, energetic shocks which can produce large amounts of CR protons via diffusive shock acceleration. We show that the energetic shocks reside mostly in the outskirts and a substantial fraction of them are induced by infall of the warm-hot intergalactic medium from filaments. As a result, the radial profile of the CR pressure in the intracluster medium is expected to be broad, dropping off more slowly than that of the gas pressure, and might be even temporarily inverted, peaking in the outskirts. The volume-integrated momentum spectrum of CR protons inside r sub(200) has the power-law slope of 4.25-4.5, indicating that the average Mach number of the shocks of main CR production is in the range of left angle bracketM sub(s)right angle bracket sub(CR) approximately 3-4. We suggest that some radio relics with relatively flat radio spectrum could be explained by primary electrons accelerated by energetic infall shocks with M sub(s) gap 3 induced in the cluster outskirts.
Gliomas are associated with high mortality because of their exceedingly invasive character. As these tumors acquire their invasiveness from low-grade tumors, it is very important to understand the ...detailed molecular mechanisms of invasion onset. Recent evidences suggest the significant role of microRNAs in tumor invasion. Thus, we hypothesized that deregulation of microRNAs may be important for the malignant progression of gliomas. We found that the aberrant expression of miR-21 is responsible for glioma invasion by disrupting the negative feedback circuit of Ras/MAPK signaling, which is mediated by Spry2. Upregulation of miR-21 was triggered by tumor microenvironmental factors such as hyaluronan and growth factors in glioma cells lacking functional phosphatase and tensin homolog (PTEN), but not harboring wild-type PTEN. Consistently with these in vitro results, Spry2 protein levels were significantly decreased in 79.7% of invasive WHO grade II-IV human glioma tissues, but not in non-invasive grade I and normal tissues. The Spry2 protein levels were not correlated with their mRNA levels, but inversely correlated with miR-21 levels. Taken together, these results suggest that the post-transcriptional regulation of Spry2 by miR-21 has an essential role on the malignant progression of human gliomas. Thus, Spry2 may be a novel therapeutic target for treating gliomas.
We propose a deep learning analysis technique with a convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness ...temperature tomography images. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm maps between
z
= 6–13. We then apply two observational effects, such as instrumental noise and limit of (spatial and depth) resolution somewhat suitable for realistic choices of the Square Kilometre Array (SKA), into the 21-cm maps. We design our deep learning model with CNN to predict the sliced-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction from our CNN model has great agreement with the true value even after coarsely smoothing with broad beam size and frequency bandwidth and heavily covered by noise with narrow beam size and frequency bandwidth. Our results show that the deep learning analyzing method has the potential to reconstruct the EoR history efficiently from the 21-cm tomography surveys in future.
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