Cluster Abundance Research Articles

Crop production correlates with soil multitrophic communities at the large spatial scale

Strong associations exist between microbial communities and soil functions in natural ecosystems at large spatial scales; however, it is unclear whether these linkages are maintained in intensively managed croplands and whether these associations influence plant productivity. We collected bulk and rhizosphere soils from wheat fields –one of the most functionally and economically important crops worldwide –across the North China Plain (~300,000 km2), and examined the relationship between species-level multitrophic taxa, functional genes and wheat productivity. Our work identified significant and positive correlations of wheat productivity to the relative abundance of multitrophic clusters (co-occurring groups of soil biota including bacteria, fungi, arbuscular mycorrhizal fungi, and nematodes), and absolute abundance of functional genes associated with carbon, nitrogen, phosphorus, and sulfur cycles. We observed significant, biologically meaningful correlations between plant productivity and the abundance of specific root-associated microbial taxa and functional genes. These important linkages were robust when considered in combination with spatial, climate, and edaphic variables. Our findings highlight the importance of soil multitrophic communities in regulating soil functional potential and plant productivity, and provide a list of key-stone functional genes, which could be targeted to promote food security and production.

Aerosols in an urban cold climate: Physical and chemical characteristics of nanoparticles

Atmospheric aerosols are of significant importance in climate change and health research. This study provides a 2-years meta dataset of real-time aerosol number and size distribution measurements in a model cold-climate city of Montreal (Canada). We provide selected information on the chemical composition and morphology of aerosols (~10 nm to 10 μm). We deployed a suite of complementary techniques such as aerosol particle sizers, MOUDI, S/TEM imaging, EDS, QQQ-ICP-MS/MS, IC, and TOC analyzers. The highest geomean nanoparticles (<100 nm) number density (9260 ± 1.6 number/cm3) was observed in the winter. A broad range of metals, including emerging contaminants, was quantified in all aerosol sizes include Pb, Cd, Ni, Zn, As, Al, Mn, Co, and Se, with concentrations ranging from 0.01 to 67.64 ng/m3. Nanosize particles included Ni, Cd, Pb, Zn. Iron exhibited the highest concentrations consistently in two modes (<180 nm and > 1 μm). S/TEM-EDS confirmed the abundance of nanoparticles, single and clusters, with multifaceted morphologies and compositions. We identified (a) emerging nanoparticles, (b) secondary organic aerosols, (c) bioaerosols, and (d) combustion particles. Diurnal, weekly, monthly, seasonal, and yearly variations of aerosols are provided. We herein discuss the implications of these results on air quality and climate modelling.

Lower PDL1, PDL2, and AXL Expression on Lung Myeloid Cells Suggests Inflammatory Bias in Smoking and Chronic Obstructive Pulmonary Disease.

Lung myeloid cells are important in pulmonary immune homeostasis and in the pathogenesis of chronic obstructive pulmonary disease (COPD). Multiparameter immunophenotypic characterization of these cells is challenging because of their autofluorescence and diversity. We evaluated the immunophenotypic landscape of airway myeloid cells in COPD using time of flight mass cytometry. Cells from BAL, which were obtained from never-smokers (n = 8) and smokers with (n = 20) and without (n = 4) spirometric COPD, were examined using a 44-parameter time of flight mass cytometry panel. Unsupervised cluster analysis was used to identify cellular subtypes that were confirmed by manual gating. We identified major populations of CD68+ and CD68- cells with 22 distinct phenotypic clusters, of which 18 were myeloid cells. We found a higher abundance of putative recruited myeloid cells (CD68+ classical monocytes) in BAL from patients with COPD. CD68+ classical monocyte population had distinct responses to smoking and COPD that were potentially related to their recruitment from the interstitium and vasculature. We demonstrate that BAL cells from smokers and subjects with COPD have lower AXL expression. Also, among subjects with COPD, we report significant differences in the abundance of PDL1high and PDL2high clusters and in the expression of PDL1 and PDL2 across several macrophage subtypes suggesting modulation of inflammatory responses. In addition, several phenotypic differences in BAL cells from subjects with history of COPD exacerbation were identified that could inform potential disease mechanisms. Overall, we report several changes to the immunophenotypic landscape that occur with smoking, COPD, and past exacerbations that are consistent with decreased regulation and increased activation of inflammatory pathways.

Single-Cell Analysis Reveals Fibroblast Clusters Linked to Immunotherapy Resistance in Cancer.

A subset of cancer-associated fibroblasts (FAP+/CAF-S1) mediates immunosuppression in breast cancers, but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 19,000 single CAF-S1 fibroblasts from breast cancer. We validate the five most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extracellular matrix proteins and TGFβ signaling, respectively, are indicative of primary resistance to immunotherapies. Cluster 0/ecm-myCAF upregulates PD-1 and CTLA4 protein levels in regulatory T lymphocytes (Tregs), which, in turn, increases CAF-S1 cluster 3/TGFβ-myCAF cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance. SIGNIFICANCE: Our work provides a significant advance in characterizing and understanding FAP+ CAF in cancer. We reached a high resolution at single-cell level, which enabled us to identify specific clusters associated with immunosuppression and immunotherapy resistance. Identification of cluster-specific signatures paves the way for therapeutic options in combination with immunotherapies.This article is highlighted in the In This Issue feature, p. 1241.

Tracing the Assembly of the Milky Way’s Disk through Abundance Clustering

Abstract A major goal in the field of galaxy formation is to understand the formation of the Milky Way’s disk. The first step toward doing this is to empirically describe its present state. We use the new high-dimensional data set of 19 abundances from 27,135 red clump Apache Point Observatory Galactic Evolution Experiment stars to examine the distribution of clusters defined using abundances. We explore different dimension reduction techniques and implement a nonparametric agglomerate hierarchical clustering method. We see that groups defined using abundances are spatially separated, as a function of age. Furthermore, the abundance groups represent different distributions in the [Fe/H]–age plane. Ordering our clusters by age reveals patterns suggestive of the sequence of chemical enrichment in the disk over time. Our results indicate that a promising avenue to trace the details of the disk’s assembly is via a full interpretation of the empirical connections we report.

Extratidal Stars and Chemical Abundance Properties of Two Metal-poor Globular Clusters M53 (NGC 5024) and NGC 5053

Abstract We search for extratidal stars around two metal-poor Galactic globular clusters, M53 and NGC 5053, using the near-infrared APOGEE spectra. Applying the t-distributed stochastic neighbor embedding (t-SNE) algorithm on the chemical abundances and radial velocities results in identification of two isolated stellar groups composed of cluster member stars in the t-SNE projection plane. With additional selection criteria of radial velocity, location in the color–magnitude diagram, and abundances from a manual chemical analysis, we find a total of 73 cluster member candidates; seven extratidal stars are found beyond the tidal radii of the two clusters. The extratidal stars around the clusters tend to be located along the leading direction of the cluster proper motion, and the individual proper motion of these stars also seems to be compatible to those of clusters. Interestingly, we find that one extratidal star of NGC 5053 is located on the southern outskirts of M53, which is part of common stellar envelope by the tidal interaction between two clusters. We discuss the nature of this star in the context of the tidal interaction between two clusters. We find apparent Mg–Al anticorrelations with a clear gap and spread (∼0.9 dex) in Al abundances for both clusters, and a light Si abundance spread (∼0.3 dex) for NGC 5053. Since all extratidal stars have Mg-enhanced and Al-depleted features, they could be first-generation stars of two globular clusters. Our results support that M53 and NGC 5053 originated in dwarf galaxies and are surrounded by extended stellar substructures of more numerous populations of clusters.

Discovery of an Abundance of Biosynthetic Gene Clusters in Shark Bay Microbial Mats.

Microbial mats are geobiological multilayered ecosystems that have significant evolutionary value in understanding the evolution of early life on Earth. Shark Bay, Australia has some of the best examples of modern microbial mats thriving under harsh conditions of high temperatures, salinity, desiccation, and ultraviolet (UV) radiation. Microorganisms living in extreme ecosystems are thought to potentially encode for secondary metabolites as a survival strategy. Many secondary metabolites are natural products encoded by a grouping of genes known as biosynthetic gene clusters (BGCs). Natural products have diverse chemical structures and functions which provide competitive advantages for microorganisms and can also have biotechnology applications. In the present study, the diversity of BGC were described in detail for the first time from Shark Bay microbial mats. A total of 1477 BGCs were detected in metagenomic data over a 20 mm mat depth horizon, with the surface layer possessing over 200 BGCs and containing the highest relative abundance of BGCs of all mat layers. Terpene and bacteriocin BGCs were highly represented and their natural products are proposed to have important roles in ecosystem function in these mat systems. Interestingly, potentially novel BGCs were detected from Heimdallarchaeota and Lokiarchaeota, two evolutionarily significant archaeal phyla not previously known to possess BGCs. This study provides new insights into how secondary metabolites from BGCs may enable diverse microbial mat communities to adapt to extreme environments.

A clustering-based self-calibration of the richness-to-mass relation of CAMIRA galaxy clusters out to z ≈ 1.1 in the Hyper Suprime-Cam survey

ABSTRACT We perform a self-calibration of the richness-to-mass (N–M) relation of CAMIRA galaxy clusters with richness N ≥ 15 at redshift 0.2 ≤ z &amp;lt; 1.1 by modelling redshift-space two-point correlation functions. These correlation functions are the autocorrelation function ξcc of CAMIRA clusters, the autocorrelation function ξgg of the CMASS galaxies spectroscopically observed in the Baryon Oscillation Spectroscopic Survey, and the cross-correlation function ξcg between these two samples. We focus on constraining the normalization AN of the N–M relation with a forward-modelling approach, carefully accounting for the redshift-space distortion, the Finger-of-God effect, and the uncertainty in photometric redshifts of CAMIRA clusters. The modelling also takes into account the projection effect on the halo bias of CAMIRA clusters. The parameter constraints are shown to be unbiased according to validation tests using a large set of mock catalogues constructed from N-body simulations. At the pivotal mass $M_{500}=10^{14}\, h^{-1}\, \mathrm{M}_{\odot }$ and the pivotal redshift zpiv = 0.6, the resulting normalization AN is constrained as $13.8^{+5.8}_{-4.2}$, $13.2^{+3.4}_{-2.7}$, and $11.9^{+3.0}_{-1.9}$ by modelling ξcc, ξcc + ξcg, and ξcc + ξcg + ξgg, with average uncertainties at levels of 36, 23, and $21{{\ \rm per\ cent}}$, respectively. We find that the resulting AN is statistically consistent with those independently obtained from weak-lensing magnification and from a joint analysis of shear and cluster abundance, with a preference for a lower value at a level of ≲ 1.9σ. This implies that the absolute mass scale of CAMIRA clusters inferred from clustering is mildly higher than those from the independent methods. We discuss the impact of the selection bias introduced by the cluster finding algorithm, which is suggested to be a subdominant factor in this work.

A statistical approach for tracking clonal dynamics in cancer using longitudinal next-generation sequencing data.

MotivationTumours are composed of distinct cancer cell populations (clones), which continuously adapt to their local micro-environment. Standard methods for clonal deconvolution seek to identify groups of mutations and estimate the prevalence of each group in the tumour, while considering its purity and copy number profile. These methods have been applied on cross-sectional data and on longitudinal data after discarding information on the timing of sample collection. Two key questions are how can we incorporate such information in our analyses and is there any benefit in doing so?ResultsWe developed a clonal deconvolution method, which incorporates explicitly the temporal spacing of longitudinally sampled tumours. By merging a Dirichlet Process Mixture Model with Gaussian Process priors and using as input a sequence of several sparsely collected samples, our method can reconstruct the temporal profile of the abundance of any mutation cluster supported by the data as a continuous function of time. We benchmarked our method on whole genome, whole exome and targeted sequencing data from patients with chronic lymphocytic leukaemia, on liquid biopsy data from a patient with melanoma and on synthetic data and we found that incorporating information on the timing of tissue collection improves model performance, as long as data of sufficient volume and complexity are available for estimating free model parameters. Thus, our approach is particularly useful when collecting a relatively long sequence of tumour samples is feasible, as in liquid cancers (e.g. leukaemia) and liquid biopsies.Availability and implementationThe statistical methodology presented in this paper is freely available at github.com/dvav/clonosGP.Supplementary information Supplementary data are available at Bioinformatics online.

Relative stability of planar clusters B11, B12, and B13 in neutral- and charged-states

Theoretically, within the diatomic model, the relative stability of most abundant boron clusters B11, B12, and B13 with planar structures in neutral, positive and negative charged-states is studied. According to the specific (per atom) binding energy criterion, B12+ (6.49 eV) is found to be the most stable boron cluster, while B11– + B13+ (5.83 eV) neutral pair is expected to present the preferable ablation channel for boron-rich solids. Obtained results would be applicable in production of boron-clusters-based nanostructured coating materials with super-properties such as lightness, hardness, conductivity, chemical inertness, neutron-absorption, etc., making them especially effective for protection against cracking, wear, corrosion, neutron- and electromagnetic-radiations, etc.

MRIP Regulates the Myosin IIA Activity and DDR1 Function to Enable Collagen Tractional Remodeling.

DDR1 is a collagen adhesion-mechanoreceptor expressed in fibrotic lesions. DDR1 mediates non-muscle myosin IIA (NMIIA)-dependent collagen remodeling. We discovered that the myosin phosphatase Rho-interacting protein (MRIP), is enriched in DDR1-NMIIA adhesions on collagen. MRIP regulates RhoA- and myosin phosphatase-dependent myosin activity. We hypothesized that MRIP regulates DDR1-NMIIA interactions to enable cell migration and collagen tractional remodeling. After deletion of MRIP in β1-integrin null cells expressing DDR1, in vitro wound closure, collagen realignment, and contraction were reduced. Cells expressing DDR1 and MRIP formed larger and more abundant DDR1 clusters on collagen than cells cultured on fibronectin or cells expressing DDR1 but null for MRIP or cells expressing a non-activating DDR1 mutant. Deletion of MRIP reduced DDR1 autophosphorylation and blocked myosin light chain-dependent contraction. Deletion of MRIP did not disrupt the association of DDR1 with NMIIA. We conclude that MRIP regulates NMIIA-dependent DDR1 cluster growth and activation. Accordingly, MRIP may provide a novel drug target for dysfunctional DDR1-related collagen tractional remodeling in fibrosis.

Beach restoration improves habitat quality for American horseshoe crabs and shorebirds in the Delaware Bay, USA

Beach nourishment is commonly conducted to protect human infrastructure but rarely for the primary purpose of improving wildlife habitat. To improve horseshoe crab spawning and shorebird feeding habitat in the Delaware Bay, New Jersey (USA), we removed 2000 t of shoreline rubble and placed sand on 16 ha of degraded shoreline spanning 8 beaches. Horseshoe crab egg cluster abundance varied annually, seasonally and spatially. Beaches restored using sand with grain size fractions similar to native sand had horseshoe crab egg cluster abundances matching or exceeding those of high-quality reference beaches. Deeper sand with a higher coarse-grain fraction resulted in the highest egg cluster abundance across all sites and beaches, while finer-grained sand used on a subset of restored beaches was associated with lower egg cluster abundances. These patterns were also reflected in shallow egg availability for shorebirds, with egg cluster abundance correlating positively with shallow egg abundance. Over time, sand placed on beaches moved cross-shore and longshore, and overwashed into marshes. Longshore sand movement nourished adjacent beaches and ebb shoals at creek mouths. Such shoals attract spawning horseshoe crabs and have high densities of surface eggs available for shorebird feeding, but experience high attrition of egg clusters. This study demonstrates that investments in beach restoration provide important benefits for horseshoe crabs and shorebirds. Outcomes can be further improved by expanding project scope and integrating other coastal restoration strategies. Restoration will be critical for the conservation of coastal species as sea levels rise and current and past coastal management practices continue to degrade habitats.

Dark Energy Survey Year 1 Results: Cosmological constraints from cluster abundances and weak lensing

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =\sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $\Omega_{\rm m}=0.179^{+0.031}_{-0.038}$, with $\sigma_8-\Omega_{\rm m}$ posteriors in $2.4\sigma$ tension with the DES Y1 3x2pt results, and in $5.6\sigma$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($\lambda \ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.

Highly Branched RG-I Domain Enrichment Is Indispensable for Pectin Mitigating against High-Fat Diet-Induced Obesity.

Obesity is associated with gut microbiome dysbiosis. Our previous research has shown that highly branched rhamnogalacturonan type I (RG-I)-enriched pectin (WRP, 531.5 kDa, 70.44% RG-I, Rha/(Gal + Ara) = 20) and its oligosaccharide with less branched RG-I [DWRP, 12.1 kDa, 50.29% RG-I, Rha/(Gal + Ara) = 6] are potential prebiotics. The present study is conducted to uncover the impact of the content, molecular size, and branch degrees of RG-I on the inhibiting effect of high-fat diet (HFD)-induced obesity. The commercial pectin (CP, 496.2 kDa, 35.77% RG-I, Rha/(Gal + Ara) = 6), WRP, and DWRP were orally administered to HFD-fed C57BL/6J mice (100 mg kg-1 d-1) to determine their individual effects on obesity. WRP significantly prevented bodyweight gain, insulin resistance, and inflammatory responses in HFD-fed mice. No obvious anti-obesity effect was observed in either CP or DWRP supplementation. A mechanistic study revealed that CP and DWRP could not enhance the diversity of gut microbiota, while WRP treatment positively modulated the gut microbiota of obese mice by increasing the abundance of Butyrivibrio, Roseburia, Barnesiella, Flavonifractor, Acetivibrio, and Clostridium cluster IV. Furthermore, WRP significantly promoted browning of white adipose tissues in HFD-fed mice, while CP and DWRP did not. WRP can attenuate the HFD-induced obesity by modulation of gut microbiota and lipid metabolism. Highly branched RG-I domain enrichment is essential for pectin mitigating against the HFD-induced obesity.

Establishing a mouse model of choroidal neovascularization to study the therapeutic effect of levotinib and its mechanism.

ObjectiveTo study the therapeutic effect and mechanism of levotinib on choroidal neovascularization (CNV) in mice.Methods45 healthy C57BL/6 mice were selected and randomly divided into three groups: control group (group A), model group (group B) and levotinib group (group C). The model of CNV in mice was established. The fluorescence leakage of choroidal lesions in mice was observed by fundus fluorescein angiography. The morphological changes of retinal vessels in mice were observed by retinal slice preparation, the pathological changes of eyeball tissues in mice were observed by hematoxylin-eosin (HE) staining, the expression of vascular endothelial growth factor (VEGF) in mice retina was detected by real-time quantitative fluorescence PCR, and the protein expression of VEGF in mice retina was detected by Western blotting.ResultOn the 7th, 14th and 21st day after modeling, compared with group B, the fluorescence leakage area of group C mice was significantly reduced, and the difference was statistically significant (P < 0.05). The morphology of retinal vessels in group A was normal. In group B, the retinal vessels showed large areas of ischemia without perfusion and abundant neovascularization clusters and capillaries. Compared with group B, the morphology of retinal vessels in group C was significantly improved. Group A mice had normal eyeball structure, group B mice had visible spindle-like damage to the inner and outer retina, while group C mice had significantly less spindle-like damage than group B. Compared with group A, group B mice had significantly higher expression of retinal VEGF and the difference was statistically significant (P < 0.05), but compared with group B mice, the expression of VEGF in the retina of mice in group C was significantly decreased, and the difference was statistically significant (P < 0.05). Compared with group A, the expression of VEGF in retina of group B mice was significantly increased, and the difference was statistically significant (P < 0.05). Compared with group B, the expression of VEGF in retina of group C mice was significantly decreased, and the difference was statistically significant (P < 0.05).ConclusionLevatinib has obvious therapeutic effect on CNV, which may be achieved by inhibiting the high expression of VEGF in CNV.

205-LB: Clinical Validation of the Implanted Prevascularized Cell Pouch as a Viable, Safe Site for Diabetes Cell Therapy

We report current clinical findings for the Cell Pouch (CP), as an implantable and retrievable medical device designed to develop a healthy vascularized tissue environment for transplantation and engraftment of therapeutic cells, which release the desired hormones for the treatment of diabetes, and other diseases. Patients with diabetes were implanted with the CP between 1-6 months, and under immunosuppression transplanted with islets isolated from donor pancreata. CPs (N=9) were explanted (between 14 -90 days post-tx). Histological sections of the explanted CPs were prepared, stained, and then reviewed by an independent pathologist for vascularization, and the presence of islets with insulin, C-peptide, and other endocrine hormones (glucagon, somatostatin) and ductal tissue (exocrine tissue) [(+) present; (++) abundant marked clusters of cells; (-) absence]. Pathology analysis revealed that 100% of the CPs were well-vascularized within a rich tissue bed. Of the CPs assessed, 89% (+ or ++) showed insulin; 78% (+ or ++) showed endocrine cells; 100% (+ or ++) showed ductal tissue. Islets were intimately related to micro-vessels in the CP tissue matrix. The amount of islets/exocrine tissue within the pre-transplant samples was similar to that found within the CPs that were explanted. With these findings, we have clinically demonstrated the vascularized Cell Pouch provides a safe and suitable, retrievable environment for the transplantation and survival of functional islets. With new emerging cellular replacement therapies as a clinical solution for all patients with diabetes, the unique Cell Pouch system solves a need to support a successful, positive clinical transplant outcome. Disclosure A.S. MacGillivary: Employee; Self; Sernova Corp. P.M. Toleikis: Board Member; Self; Sernova Corp. Employee; Self; Sernova Corp. Stock/Shareholder; Self; Sernova Corp. D.M. Mazzuca: Employee; Self; Sernova Corp. Stock/Shareholder; Self; Sernova Corp.

Formation of Nanoclusters in Gold Nucleation

Gold nanoclusters consisting of a specific atom number have gained popularity in research in recent years due to their outstanding properties. Due to their molecule-like behavior, their properties depend strongly on their size. Although they represent the link species between atoms and nanoparticles and are the subject of current research, a high-resolution characterization is still missing. Here, we used the band forming experiment in analytical ultracentrifugation (AUC) to characterize the gold nanoclusters in the moment of their generation using thioglycerol as a stabilizer. The concentration variation of the gold precursor, reducing agent, and stabilizer was investigated. The formation of different cluster species from the smallest Au4 up to Au911 could be observed. Very stable clusters of Au55 appear in every experiment and other cluster sizes more rarely. The extracted UV/Vis spectra could additionally be correlated to every cluster. The variation in the concentration of sodium borohydride and the stabilizer did not lead to a clear trend, but the gold ion concentration directed the size of the formed clusters. A decrease seemed to promote the generation of a higher abundance of smaller clusters accompanied by less big clusters, and vice versa. These results present the characterization of the different nanocluster generations directly in the formation process of nanoparticles and therefore are a contribution to the understanding of their formation.

Abundance, Functional, and Evolutionary Analysis of Oxalyl-Coenzyme A Decarboxylase in Human Microbiota.

Oxalic acid and its oxalate salts have been linked to kidney stones and other health problems and about 80% kidney stones are made up of calcium oxalate. Oxalyl coenzyme A decarboxylase (OXC) is a key enzyme in the catabolism of oxalate. In this study, we performed bioinformatic and biochemical analysis of OXC. First, we mined the OXC sequences from a public protein database and collected 1396 putative OXC sequences. These sequences were widely spread and mainly distributed in Actinobacteria, Alphaproteobacteria, Gammaproteobacteria, and Betaproteobacteria and classified into seven clusters. The phylogenetic relationship and evolutionary rate of the 7 clusters showed that OXC are highly conserved. Second, the abundance of the different clusters of OXC was explored in 380 human microbiome datasets, which showed that OXCs in Cluster 1 were relatively high in the gut while OXCs in Clusters 2–4 were relatively enriched in the vagina. Third, we measured the activity of one OXC from Mycobacterium mageritense (OXCmm) in Cluster 3, in which there was no experimentally characterized enzymes. Mutation analysis showed that OXCmm shared the same active sites with the OXC from Oxalobacter formigenes. Taken together, this analysis provides a better insight into the distribution and catalysis of OXC and further potential alternative application of OXC active bacteria as probiotics in the management of kidney stone disease.

Variable-Length Subsequence Clustering in Time Series

Subsequence clustering is an important issue in time series data mining. Observing that most time series consist of various patterns with different unknown lengths, we propose an optimization framework to adaptively estimate the lengths and representations for different patterns. Our framework minimizes the inner subsequence cluster errors with respect to subsequence clusters and segmentation under time series cover constraint where the subsequence cluster lengths can be variable. To optimize our framework, we first generate abundant initial subsequence clusters with different lengths. Then, three cluster operations, i.e., cluster splitting, combination and removing, are used to iteratively refine the cluster lengths and representations by respectively splitting clusters consisting of different patterns, joining neighboring clusters belonging to the same pattern and removing clusters to the predefined cluster number. During each cluster refinement, we employ an efficient algorithm to alternatively optimize subsequence clusters and segmentation based on dynamic programming. Our method can automatically and efficiently extract the unknown variable-length subsequence clusters in the time series. Comparative results with the state-of-the-art are conducted on various synthetic and real time series, and quantitative and qualitative performances demonstrate the effectiveness of our method.

Cosmology dependence of galaxy cluster scaling relations

ABSTRACT The abundance of galaxy clusters as a function of mass and redshift is a well known powerful cosmological probe, which relies on underlying modelling assumptions on the mass-observable relations (MOR). Some of the MOR parameters can be constrained directly from multi-wavelength observations, as the normalization at some reference cosmology, the mass-slope, the redshift evolution, and the intrinsic scatter. However, the cosmology dependence of MORs cannot be tested with multi-wavelength observations alone. We use magneticum simulations to explore the cosmology dependence of galaxy cluster scaling relations. We run fifteen hydrodynamical cosmological simulations varying Ωm, Ωb, h0, and σ8 (around a reference cosmological model). The MORs considered are gas mass, baryonic mass, gas temperature, Y and velocity dispersion as a function of virial mass. We verify that the mass and redshift slopes and the intrinsic scatter of the MORs are nearly independent of cosmology with variations significantly smaller than current observational uncertainties. We show that the gas mass and baryonic mass sensitively depends only on the baryon fraction, velocity dispersion, and gas temperature on h0, and Y on both baryon fraction and h0. We investigate the cosmological implications of our MOR parametrization on a mock catalogue created for an idealized eROSITA-like experiment. We show that our parametrization introduces a strong degeneracy between the cosmological parameters and the normalization of the MOR. Finally, the parameter constraints derived at different overdensity (Δ500c), for X-ray bolometric gas luminosity, and for different subgrid physics prescriptions are shown in the appendix.