How to make compost and (help) save the world.

The Studio City home of late composer Jack Smalley, whose credits include 'Murder, She Wrote' and 'The Last of the Mohicans,' is for sale.

Anthony Davis shares the accidentally amusing way he learned that "The Central Park Five," which premiered at Long Beach Opera, had won the Pulitzer.

Essex County OPP have released a composite drawing of a suspect reported to be impersonating a police officer in Lakeshore.

Joe Carroll
Feb 1, 2003; 2:117-126
Research

Dongming Wang, Rina Dong and Chenqi Mou
Math. Comp. 89 (2020), 1993-2015.
Abstract, references and article information

Ning Zhang, Jia Wu and Liwei Zhang
Math. Comp. 89 (2020), 1867-1894.
Abstract, references and article information

Jiangxue Fang
Trans. Amer. Math. Soc. 373 (2020), 3445-3481.
Abstract, references and article information

Yu. K. Dem'yanovich
St. Petersburg Math. J. 31 (2020), 435-453.
Abstract, references and article information

Tonie Fares and Pascal Lefèvre
Proc. Amer. Math. Soc. 148 (2020), 2487-2496.
Abstract, references and article information

S. Waleed Noor and Osmar R. Severiano
Proc. Amer. Math. Soc. 148 (2020), 2469-2476.
Abstract, references and article information

Joseph Reid
Proc. Amer. Math. Soc. 148 (2020), 2331-2343.
Abstract, references and article information

Joachim Kock and David I. Spivak
Proc. Amer. Math. Soc. 148 (2020), 2317-2329.
Abstract, references and article information

(Princeton University, Engineering School) New findings about critical cellular structures have upended common assumptions about their formation and composition and provided new insight how molecular machines are built in living cells.

Do you know which main gases are contained in the composition of air? Under climate change and global warming, carbon dioxide ...

Perlecan is a critical proteoglycan found in the extracellular matrix (ECM) of cartilage. In healthy cartilage, perlecan regulates cartilage biomechanics and we previously demonstrated perlecan deficiency leads to reduced cellular and ECM stiffness in vivo. This change in mechanics may lead to the early onset osteoarthritis seen in disorders resulting from perlecan knockdown such as Schwartz-Jampel syndrome (SJS). To identify how perlecan knockdown affects the material properties of developing cartilage, we used imaging and liquid chromatography–tandem mass spectrometry (LC-MS/MS) to study the ECM in a murine model of SJS, Hspg2C1532Y-Neo. Perlecan knockdown led to defective pericellular matrix formation, whereas the abundance of bulk ECM proteins, including many collagens, increased. Post-translational modifications and ultrastructure of collagens were not significantly different; however, LC-MS/MS analysis showed more protein was secreted by Hspg2C1532Y-Neo cartilage in vitro, suggesting that the incorporation of newly synthesized ECM was impaired. In addition, glycosaminoglycan deposition was atypical, which may explain the previously observed decrease in mechanics. Overall, these findings provide insight into the influence of perlecan on functional cartilage assembly and the progression of osteoarthritis in SJS.

Atherosclerosis-related CVD causes nearly 20 million deaths annually. Most patients are treated after plaques develop, so therapies must regress existing lesions. Current therapies reduce plaque volume, but targeting all apoB-containing lipoproteins with intensive combinations that include alirocumab or evinacumab, monoclonal antibodies against cholesterol-regulating proprotein convertase subtilisin/kexin type 9 and angiopoietin-like protein 3, may provide more benefit. We investigated the effect of such lipid-lowering interventions on atherosclerosis in APOE*3-Leiden.CETP mice, a well-established model for hyperlipidemia. Mice were fed a Western-type diet for 13 weeks and thereafter matched into a baseline group (euthanized at 13 weeks) and five groups that received diet alone (control) or with treatment [atorvastatin; atorvastatin and alirocumab; atorvastatin and evinacumab; or atorvastatin, alirocumab, and evinacumab (triple therapy)] for 25 weeks. We measured effects on cholesterol levels, plaque composition and morphology, monocyte adherence, and macrophage proliferation. All interventions reduced plasma total cholesterol (37% with atorvastatin to 80% with triple treatment; all P < 0.001). Triple treatment decreased non-HDL-C to 1.0 mmol/l (91% difference from control; P < 0.001). Atorvastatin reduced atherosclerosis progression by 28% versus control (P < 0.001); double treatment completely blocked progression and diminished lesion severity. Triple treatment regressed lesion size versus baseline in the thoracic aorta by 50% and the aortic root by 36% (both P < 0.05 vs. baseline), decreased macrophage accumulation through reduced proliferation, and abated lesion severity. Thus, high-intensive cholesterol-lowering triple treatment targeting all apoB-containing lipoproteins regresses atherosclerotic lesion area and improves lesion composition in mice, making it a promising potential approach for treating atherosclerosis.

The composition-function relationship of HDL particles and its effects on the mechanisms driving coronary heart disease (CHD) is poorly understood. We tested the hypothesis that the functionality of HDL particles is significantly influenced by their lipid composition. Using a novel 3D-separation method, we isolated five different-sized HDL subpopulations from CHD patients who had low preβ-1 functionality (low-F) (ABCA1-dependent cholesterol-efflux normalized for preβ-1 concentration) and controls who had either low-F or high preβ-1 functionality (high-F). Molecular numbers of apoA-I, apoA-II, and eight major lipid classes were determined in each subpopulation by LC-MS. The average number of lipid molecules decreased from 422 in the large spherical α-1 particles to 57 in the small discoid preβ-1 particles. With decreasing particle size, the relative concentration of free cholesterol (FC) decreased in α-mobility but not in preβ-1 particles. Preβ-1 particles contained more lipids than predicted; 30% of which were neutral lipids (cholesteryl ester and triglyceride), indicating that these particles were mainly remodeled from larger particles not newly synthesized. There were significant correlations between HDL-particle functionality and the concentrations of several lipids. Unexpectedly, the phospholipid:FC ratio was significantly correlated with large-HDL-particle functionality but not with preβ-1 functionality. There was significant positive correlation between particle functionality and total lipids in high-F controls, indicating that the lipid-binding capacity of apoA-I plays a major role in the cholesterol efflux capacity of HDL particles. Functionality and lipid composition of HDL particles are significantly correlated and probably both are influenced by the lipid-binding capacity of apoA-I.

Paris : J.-B. Baillière, 1870.

Paris : Béchet jeune, 1827-1829.

Edinburgh : Bell & Bradfute, 1813.

Patrick L. Combettes, Christian L. Müller.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 207--238.

Abstract:
We introduce a flexible optimization model for maximum likelihood-type estimation (M-estimation) that encompasses and generalizes a large class of existing statistical models, including Huber’s concomitant M-estimator, Owen’s Huber/Berhu concomitant estimator, the scaled lasso, support vector machine regression, and penalized estimation with structured sparsity. The model, termed perspective M-estimation, leverages the observation that convex M-estimators with concomitant scale as well as various regularizers are instances of perspective functions, a construction that extends a convex function to a jointly convex one in terms of an additional scale variable. These nonsmooth functions are shown to be amenable to proximal analysis, which leads to principled and provably convergent optimization algorithms via proximal splitting. We derive novel proximity operators for several perspective functions of interest via a geometrical approach based on duality. We then devise a new proximal splitting algorithm to solve the proposed M-estimation problem and establish the convergence of both the scale and regression iterates it produces to a solution. Numerical experiments on synthetic and real-world data illustrate the broad applicability of the proposed framework.

Tensor Train decomposition is used across many branches of machine learning. We present T3F—a library for Tensor Train decomposition based on TensorFlow. T3F supports GPU execution, batch processing, automatic differentiation, and versatile functionality for the Riemannian optimization framework, which takes into account the underlying manifold structure to construct efficient optimization methods. The library makes it easier to implement machine learning papers that rely on the Tensor Train decomposition. T3F includes documentation, examples and 94% test coverage.

Spatial trajectories are ubiquitous and complex signals. Their analysis is crucial in many research fields, from urban planning to neuroscience. Several approaches have been proposed to cluster trajectories. They rely on hand-crafted features, which struggle to capture the spatio-temporal complexity of the signal, or on Artificial Neural Networks (ANNs) which can be more efficient but less interpretable. In this paper we present a novel ANN architecture designed to capture the spatio-temporal patterns characteristic of a set of trajectories, while taking into account the demographics of the navigators. Hence, our model extracts markers linked to both behaviour and demographics. We propose a composite signal analyser (CompSNN) combining three simple ANN modules. Each of these modules uses different signal representations of the trajectory while remaining interpretable. Our CompSNN performs significantly better than its modules taken in isolation and allows to visualise which parts of the signal were most useful to discriminate the trajectories.

Uncertainties in a structure is inevitable, which generally lead to variation in dynamic response predictions. For a complex structure, brute force Monte Carlo simulation for response variation analysis is infeasible since one single run may already be computationally costly. Data driven meta-modeling approaches have thus been explored to facilitate efficient emulation and statistical inference. The performance of a meta-model hinges upon both the quality and quantity of training dataset. In actual practice, however, high-fidelity data acquired from high-dimensional finite element simulation or experiment are generally scarce, which poses significant challenge to meta-model establishment. In this research, we take advantage of the multi-level response prediction opportunity in structural dynamic analysis, i.e., acquiring rapidly a large amount of low-fidelity data from reduced-order modeling, and acquiring accurately a small amount of high-fidelity data from full-scale finite element analysis. Specifically, we formulate a composite neural network fusion approach that can fully utilize the multi-level, heterogeneous datasets obtained. It implicitly identifies the correlation of the low- and high-fidelity datasets, which yields improved accuracy when compared with the state-of-the-art. Comprehensive investigations using frequency response variation characterization as case example are carried out to demonstrate the performance.

Boyu Ren, Sergio Bacallado, Stefano Favaro, Tommi Vatanen, Curtis Huttenhower, Lorenzo Trippa.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 494--517.

Abstract:
Detecting associations between microbial compositions and sample characteristics is one of the most important tasks in microbiome studies. Most of the existing methods apply univariate models to single microbial species separately, with adjustments for multiple hypothesis testing. We propose a Bayesian analysis for a generalized mixed effects linear model tailored to this application. The marginal prior on each microbial composition is a Dirichlet process, and dependence across compositions is induced through a linear combination of individual covariates, such as disease biomarkers or the subject’s age, and latent factors. The latent factors capture residual variability and their dimensionality is learned from the data in a fully Bayesian procedure. The proposed model is tested in data analyses and simulation studies with zero-inflated compositions. In these settings and within each sample, a large proportion of counts per microbial species are equal to zero. In our Bayesian model a priori the probability of compositions with absent microbial species is strictly positive. We propose an efficient algorithm to sample from the posterior and visualizations of model parameters which reveal associations between covariates and microbial compositions. We evaluate the proposed method in simulation studies, and then analyze a microbiome dataset for infants with type 1 diabetes which contains a large proportion of zeros in the sample-specific microbial compositions.

John R. Tipton, Mevin B. Hooten, Connor Nolan, Robert K. Booth, Jason McLachlan.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2363--2388.

Abstract:
Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framework for modeling functional responses with respect to a covariate without assuming a functional form. Many scientific disciplines use Gaussian process approximations to improve prediction and make inference on latent processes and parameters. When prediction is desired on unobserved covariates given realizations of the response variable, this is called inverse prediction. Because inverse prediction is often mathematically and computationally challenging, predicting unobserved covariates often requires fitting models that are different from the hypothesized generative model. We present a novel computational framework that allows for efficient inverse prediction using a Gaussian process approximation to generative models. Our framework enables scientific learning about how the latent processes co-vary with respect to covariates while simultaneously providing predictions of missing covariates. The proposed framework is capable of efficiently exploring the high dimensional, multi-modal latent spaces that arise in the inverse problem. To demonstrate flexibility, we apply our method in a generalized linear model framework to predict latent climate states given multivariate count data. Based on cross-validation, our model has predictive skill competitive with current methods while simultaneously providing formal, statistical inference on the underlying community dynamics of the biological system previously not available.

Piotr Kokoszka, Neda Mohammadi Jouzdani.

Source: Bernoulli, Volume 26, Number 3, 2383--2399.

Abstract:
This paper is concerned with frequency domain theory for functional time series, which are temporally dependent sequences of functions in a Hilbert space. We consider a variance decomposition, which is more suitable for such a data structure than the variance decomposition based on the Karhunen–Loéve expansion. The decomposition we study uses eigenvalues of spectral density operators, which are functional analogs of the spectral density of a stationary scalar time series. We propose estimators of the variance components and derive convergence rates for their mean square error as well as their asymptotic normality. The latter is derived from a frequency domain invariance principle for the estimators of the spectral density operators. This principle is established for a broad class of linear time series models. It is a main contribution of the paper.

Akio Fujiwara, Koichi Yamagata.

Source: Bernoulli, Volume 26, Number 3, 2105--2142.

Abstract:
We herein develop a theory of contiguity in the quantum domain based upon a novel quantum analogue of the Lebesgue decomposition. The theory thus formulated is pertinent to the weak quantum local asymptotic normality introduced in the previous paper [Yamagata, Fujiwara, and Gill, Ann. Statist. 41 (2013) 2197–2217], yielding substantial enlargement of the scope of quantum statistics.

Fiona Doetsch
Jul 1, 1997; 17:5046-5061
Articles

The World pairs champion and Olympic gold medallist played the piano during a special hosted by fellow Canadian figure skater Kaitlyn Weaver, to raise funds for the United Nation's COVID-19 Solidarity Response Fund.

The following is a guest post from Music Reference Specialist James Wintle. Let me begin with a personal anecdote. My parents are or were both musicians – my father was a composer – and so my appreciation for classical music was probably equal parts nature and nurture. So, when I entered graduate school as a […]

Every day there is something or the other happening in the entertainment industry the proceeds of which are being given away for fighting the corona crisis.

The direct effects of prolactin on the nutritional and antimicrobial composition of breast milk have not been examined previously in women.

The study demonstrates that recombinant human prolactin increases milk volume, induces changes in milk composition consistent with those during normal lactogenesis, and increases antimicrobially active oligosaccharide concentrations. The data suggest that prolactin is an important mediator of normal lactogenesis. (Read the full article)

Dental composites composed of bisphenol A (BPA) derivatives are common alternatives to amalgam, but may release BPA. Gestational BPA exposure has been associated with poorer behavior in children. A safety trial of amalgam found worse psychosocial outcomes for children randomized to composites.

In the trial, greater exposure to bisphenol-A-glycidyl-methacrylate-based dental composite in children aged 6 to 10 years was associated with worse self-reported psychosocial functioning at 5-year follow-up. There were no such associations with exposure to dental amalgam or urethane-dimethacrylate-based polyacid-modified composite (compomer). (Read the full article)

The traditional process-focused approach to quality improvement has not remedied NICUs’ inconsistency in quality of care delivery across clinically important measures. Global measurement of quality may induce broad, systems-based improvement, but must be formally studied.

We present a systematically developed and robust composite indicator, the Baby-MONITOR, to assess the quality of care delivered to very low birth weight infants in the NICU setting. (Read the full article)

John Penders
Aug 1, 2006; 118:511-521
ARTICLES

elaware residents may pre-order environmentally beneficial compost bins and rain barrels at discount prices during an online sale in May. Made available by DNREC’s Division of Waste & Hazardous Substances, in conjunction with the Division of Watershed Stewardship, advance purchases must be made for both items at www.enviroworld.us/delaware

While big tech has shouldered the load, the Nasdaq Composite is also home to 700 health-care and biotechnology companies that have stoked investor interest as they search for ways to treat the coronavirus.

Alarmed by the amount of rubbish they were generating by just drinking coffee and eating cup noodles, two former garments entrepreneurs decided it was time to find an eco-friendly alternative to all the plastic packaging that ends up in landfills globally.George Chen Dah-ren and Vivian Chang first approached material scientists in Hong Kong and mainland China, and were in 2013 pointed in the direction of Alexander Bismarck, then a Materials Science professor at Imperial College London. The…

ABSTRACT

Aquifers, which are essential underground freshwater reservoirs worldwide, are understudied ecosystems that harbor diverse forms of microbial life. This study investigated the abundance and composition of prokaryotic and viral communities in the outflow of five springs across northern Florida, USA, as a proxy of microbial communities found in one of the most productive aquifers in the world, the Floridan aquifer. The average abundances of virus-like particles and prokaryotic cells were slightly lower than those reported from other groundwater systems, ranging from 9.6 x 10³ ml^–1 to 1.1 x 10⁵ ml^–1 and 2.2 x 10³ ml^–1 to 3.4 x 10⁴ ml^–1, respectively. Despite all of the springs being fed by the Floridan aquifer, sequencing of 16S rRNA genes and viral metagenomes (viromes) revealed unique communities in each spring, suggesting that groundwater microbial communities are influenced by land usage in recharge zones. The prokaryotic communities were dominated by Bacteria, and though the most abundant phyla (Proteobacteria, Cyanobacteria, and Bacteroidetes) were found in relatively high abundance across springs, variation was seen at finer taxonomic resolution. The viral sequences were most similar to those described from other aquatic environments. Sequencing resulted in the completion of 58 novel viral genomes representing members of the order Caudovirales as well as prokaryotic and eukaryotic single-stranded DNA (ssDNA) viruses. Sequences similar to those of ssDNA viruses were detected at all spring sites and dominated the identifiable sequences at one spring site, showing that these small viruses merit further investigation in groundwater systems.

IMPORTANCE Aquifer systems may hold up to 40% of the total microbial biomass on Earth. However, little is known about the composition of microbial communities within these critical freshwater ecosystems. Here, we took advantage of Florida’s first-magnitude springs (the highest spring classification based on water discharge), each discharging at least 246 million liters of water each day from the Floridan aquifer system (FAS), to investigate prokaryotic and viral communities from the aquifer. The FAS serves as a major source of potable water in the Southeastern United States, providing water for large cities and citizens in three states. Unfortunately, the health of the FAS and its associated springs has declined in the past few decades due to nutrient loading, increased urbanization and agricultural activity in aquifer recharge zones, and saltwater intrusion. This is the first study to describe the prokaryotic and viral communities in Florida’s first-magnitude springs, providing a baseline against which to compare future ecosystem change.

ABSTRACT

Bacteria that encounter antibiotics can efficiently change their physiology to develop resistance. This intrinsic antibiotic resistance is mediated by multiple pathways, including a regulatory system(s) that activates specific genes. In some Streptomyces and Mycobacterium spp., the WblC/WhiB7 transcription factor is required for intrinsic resistance to translation-targeting antibiotics. Wide conservation of WblC/WhiB7 within Actinobacteria indicates a critical role of WblC/WhiB7 in developing resistance to such antibiotics. Here, we identified 312 WblC target genes in Streptomyces coelicolor, a model antibiotic-producing bacterium, using a combined analysis of RNA sequencing and chromatin immunoprecipitation sequencing. Interestingly, WblC controls many genes involved in translation, in addition to previously identified antibiotic resistance genes. Moreover, WblC promotes translation rate during antibiotic stress by altering the ribosome-associated protein composition. Our genome-wide analyses highlight a previously unappreciated antibiotic resistance mechanism that modifies ribosome composition and maintains the translation rate in the presence of sub-MIC levels of antibiotics.

IMPORTANCE The emergence of antibiotic-resistant bacteria is one of the top threats in human health. Therefore, we need to understand how bacteria acquire resistance to antibiotics and continue growth even in the presence of antibiotics. Streptomyces coelicolor, an antibiotic-producing soil bacterium, intrinsically develops resistance to translation-targeting antibiotics. Intrinsic resistance is controlled by the WblC/WhiB7 transcription factor that is highly conserved within Actinobacteria, including Mycobacterium tuberculosis. Here, identification of the WblC/WhiB7 regulon revealed that WblC/WhiB7 controls ribosome maintenance genes and promotes translation in the presence of antibiotics by altering the composition of ribosome-associated proteins. Also, the WblC-mediated ribosomal alteration is indeed required for resistance to translation-targeting antibiotics. This suggests that inactivation of the WblC/WhiB7 regulon could be a potential target to treat antibiotic-resistant mycobacteria.

ABSTRACT

The chemical structures of soluble fiber carbohydrates vary from source to source due to numerous possible linkage configurations among monomers. However, it has not been elucidated whether subtle structural variations might impact soluble fiber fermentation by colonic microbiota. In this study, we tested the hypothesis that subtle structural variations in a soluble polysaccharide govern the community structure and metabolic output of fermenting microbiota. We performed in vitro fecal fermentation studies using arabinoxylans (AXs) from different classes of wheat (hard red spring [AX_HRS], hard red winter [AX_HRW], and spring red winter [AX_SRW]) with identical initial microbiota. Carbohydrate analyses revealed that AX_SRW was characterized by a significantly shorter backbone and increased branching compared with those of the hard varieties. Amplicon sequencing demonstrated that fermentation of AX_SRW resulted in a distinct community structure of significantly higher richness and evenness than those of hard-AX-fermenting cultures. AX_SRW favored OTUs within Bacteroides, whereas AX_HRW and AX_HRS favored Prevotella. Accordingly, metabolic output varied between hard and soft varieties; higher propionate production was observed with AX_SRW and higher butyrate and acetate with AX_HRW and AX_HRS. This study showed that subtle changes in the structure of a dietary fiber may strongly influence the composition and function of colonic microbiota, further suggesting that physiological functions of dietary fibers are highly structure dependent. Thus, studies focusing on interactions among dietary fiber, gut microbiota, and health outcomes should better characterize the structures of the carbohydrates employed.

IMPORTANCE Diet, especially with respect to consumption of dietary fibers, is well recognized as one of the most important factors shaping the colonic microbiota composition. Accordingly, many studies have been conducted to explore dietary fiber types that could predictably manipulate the colonic microbiota for improved health. However, the majority of these studies underappreciate the vastness of fiber structures in terms of their microbial utilization and omit detailed carbohydrate structural analysis. In some cases, this causes conflicting results to arise between studies using (theoretically) the same fibers. In this investigation, by performing in vitro fecal fermentation studies using bran arabinoxylans obtained from different classes of wheat, we showed that even subtle changes in the structure of a dietary fiber result in divergent microbial communities and metabolic outputs. This underscores the need for much higher structural resolution in studies investigating interactions of dietary fibers with gut microbiota, both in vitro and in vivo.

Glass is the favorite material for parenteral packaging because of its physico-chemical properties. Type I borosilicate glass is worldwide use at this scope, but it may have some issues related to breakage, corrosion and delamination that might compromise the drug quality, safety and efficacy. These issues can be mitigated and avoided starting from the appropriate selection of the most suitable raw material at the early stage of the glass container design. In this study, Type I borosilicate glass vials manufactured using two glass tubes having different chemical compositions, were studied and compared in terms of their resistance to corrosion. Testing design was applied with the aim to select the best practice approach comparing different storage simulation conditions: ageing treatment through autoclaving and stability testing (real-time and accelerated). Clear differences were found between the different glass types in terms of hydrolytic and corrosion resistance that highlighted the relation between chemical composition and glass chemical durability. Non-negligible differences were also observed using different storage conditions.

Accumulation of lipid in skeletal muscle is thought to be related to the development of insulin resistance and type 2 diabetes. Initial work in this area focused on accumulation of intramuscular triglyceride; however, bioactive lipids such as diacylglycerols and sphingolipids are now thought to play an important role. Specific species of these lipids appear to be more negative toward insulin sensitivity than others. Adding another layer of complexity, localization of lipids within the cell appears to influence the relationship between these lipids and insulin sensitivity. This article summarizes how accumulation of total lipids, specific lipid species, and localization of lipids influence insulin sensitivity in humans. We then focus on how these aspects of muscle lipids are impacted by acute and chronic aerobic and resistance exercise training. By understanding how exercise alters specific species and localization of lipids, it may be possible to uncover specific lipids that most heavily impact insulin sensitivity.

This study investigated the effects of long-term soil fertilization on the composition and potential for phosphorus (P) and nitrogen (N) cycling of bacterial communities associated with hyphae of the P-solubilizing fungus Penicillium canescens. Using a baiting approach, hyphosphere bacterial communities were recovered from three soils that had received long-term amendment in the field with mineral or mineral plus organic fertilizers. P. canescens hyphae recruited bacterial communities with a decreased diversity and an increased abundance of Proteobacteria relative to what was observed in soil communities. As core bacterial taxa, Delftia and Pseudomonas spp. were present in all hyphosphere samples irrespective of soil fertilization. However, the type of fertilization showed significant impacts on the diversity, composition, and distinctive taxa/operational taxonomic units (OTUs) of hyphosphere communities. The soil factors P (Olsen method), exchangeable Mg, exchangeable K, and pH were important for shaping soil and hyphosphere bacterial community compositions. An increased relative abundance of organic P metabolism genes was found in hyphosphere communities from soil that had not received P fertilizers, which could indicate P limitation near the fungal hyphae. Additionally, P. canescens hyphae recruited bacterial communities with a higher abundance of N fixation genes than found in soil communities, which might imply a role of hyphosphere communities for fungal N nutrition. Furthermore, the relative abundances of denitrification genes were greater in several hyphosphere communities, indicating an at least partly anoxic microenvironment with a high carbon-to-N ratio around the hyphae. In conclusion, soil fertilization legacy shapes P. canescens hyphosphere microbiomes and their functional potential related to P and N cycling.

IMPORTANCE P-solubilizing Penicillium strains are introduced as biofertilizers to agricultural soils to improve plant P nutrition. Currently, little is known about the ecology of these biofertilizers, including their interactions with other soil microorganisms. This study shows that communities dominated by Betaproteobacteria and Gammaproteobacteria colonize P. canescens hyphae in soil and that the compositions of these communities depend on the soil conditions. The potential of these communities for N and organic P cycling is generally higher than that of soil communities. The high potential for organic P metabolism might complement the ability of the fungus to solubilize inorganic P, and it points to the hyphosphere as a hot spot for P metabolism. Furthermore, the high potential for N fixation could indicate that P. canescens recruits bacteria that are able to improve its N nutrition. Hence, this community study identifies functional groups relevant for the future optimization of next-generation biofertilizer consortia for applications in soil.

Although ample evidence indicates that immune cell homeostasis is an important prognostic outcome determinant in patients with cancer, few studies have examined whether it also determines cancer risk among initially healthy individuals. We performed a case–cohort study including incident cases of breast (n = 207), colorectal (n = 111), lung (n = 70), and prostate (n = 201) cancer as well as a subcohort (n = 465) within the European Prospective Investigation into Cancer and Nutrition-Heidelberg cohort. Relative counts of neutrophils, monocytes, and lymphocyte sublineages were measured by qRT-PCR. HRs and 95% confidence intervals were used to measure the associations between relative counts of immune cell and cancer risks. When relative counts of immune cell types were taken individually, a significant positive association was observed between relative counts of FOXP3+ regulatory T cells (Tregs) and lung cancer risk, and significant inverse associations were observed between relative CD8+ counts and risks of lung and breast cancer (overall and ER+ subtype). Multivariable models with mutual adjustments across immune markers showed further significant positive associations between higher relative FOXP3+ T-cell counts and increased risks of colorectal and breast cancer (overall and ER− subtype). No associations were found between immune cell composition and prostate cancer risk. These results affirm the relevance of elevated FOXP3+ Tregs and lower levels of cytotoxic (CD8+) T cells as risk factors for tumor development.Significance:This epidemiologic study supports a role for both regulatory and cytotoxic T cells in determining cancer risk among healthy individuals.See related commentary by Song and Tworoger, p. 1801

BACKGROUND AND PURPOSE:

Detailed insight into the composition of thrombi retrieved from patients with ischemic stroke by mechanical thrombectomy might improve pathophysiologic understanding and therapy. Thus, this study searched for links between histologic thrombus composition and stroke subtypes and mechanical thrombectomy results.