<ns4:p>High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level analysis complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition in different conditions. The reads have be denoised assigned closest taxa from reference database. Common approaches use notion 97% similarity normalize data by subsampling equalize library sizes. In this paper, we show that statistical...

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level analysis complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition in different conditions. The reads have be denoised assigned closest taxa from reference database. Common approaches use notion 97% similarity normalize data by subsampling equalize library sizes. In this paper, we show that statistical...

Human natural killer cell diversity is a metric of immune function associated with less effective antiviral response.

Spatial and temporal patterns in microbial communities provide insights into the forces that shape them, their functions roles health disease. Here, we used spatial ecological statistics to analyze role saliva plays structuring bacterial of human mouth using >9000 dental mucosal samples. We show regardless tissue type (teeth, alveolar mucosa, keratinized gingiva, or buccal mucosa), surface-associated vary along an gradient from front back mouth, on exposed tooth surfaces, is pronounced...

Although CD36 is generally recognized to be an inhibitory signaling receptor for thrombospondin-1 (TSP1), the molecular mechanism transduction of this signal remains unclear. Based on evidence that myristic acid and TSP1 each modulate endothelial cell nitric oxide in a CD36-dependent manner, we examined ability fatty translocase activity CD36. antibody mimics inhibited myristate uptake. Recombinant type 1 repeats were weakly inhibitory, but anti-angiogenic peptide derived from domain...

Pregnant women experience increased morbidity and mortality after influenza infection, for reasons that are not understood. Although some data suggest natural killer (NK)- T-cell responses suppressed during pregnancy, influenza-specific have been previously evaluated. Thus, we analyzed the of were pregnant (n = 21) versus those 29) immediately before inactivated vaccination (IIV), 7 d vaccination, 6 wk postpartum. Expression CD107a (a marker cytolysis) production IFN-γ macrophage...

Our work focuses on the stability, resilience, and response to perturbation of bacterial communities in human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed executed such disturbance volunteers dense longitudinal sampling scheme extending before after diarrhea. This experiment has enabled careful multidomain analysis controlled gut microbiota with new level resolution. These...

Inactivated influenza vaccine (IIV) is recommended during pregnancy to prevent infection and its complications in pregnant women their infants. However, the extent which modifies antibody response vaccination remains unclear, prior studies have focused primarily on hemagglutinin inhibition (HI) titers. A more comprehensive understanding of how humoral immune will aid maximizing efficacy.Healthy control were studied to, 7 days after, 28 after with IIV. HI titers, microneutralization (MN)...

Somatic hypermutation (SHM) is the diversity-generating process in antibody affinity maturation. Probabilistic models of SHM are needed for analyzing rare mutations, understanding selective forces guiding maturation, and underlying biochemical process. High throughput data offers potential to develop fit on relevant sets. In this paper we model using modern frameworks. We motivated by recent work suggesting importance a wider context SHM, however, assigning an independent rate each k-mer...

Somatic hypermutation (SHM) is the diversity-generating process in antibody affinity maturation. Probabilistic models of SHM are needed for analyzing rare mutations, understanding selective forces guiding maturation, and underlying biochemical process. High throughput data offers potential to develop fit on relevant sets. In this paper we model using modern frameworks. We motivated by recent work suggesting importance a wider context SHM, however, assigning an independent rate each k-mer...

Background Natural killer (NK) cells have antiviral and antitumor activity that could be harnessed for the treatment of infections malignancies. To maintain cell viability enhance effects, NK are frequently treated with cytokines. Here they performed an extensive assessment effects cytokines on phenotype function human cells. Methods They used cytometry by time‐of‐flight (CyTOF) to evaluate repertoire changes after stimulation interleukin (IL)‐2, IL‐15 or a combination IL‐12/IL‐15/IL‐18....

Phylogenetically informed distances are commonly used in the analysis of microbiome data, and analysts have many options to choose from. Although all phylogenetic share goal incorporating relationships among bacteria, they do so different ways give pictures between bacterial communities.We investigate properties two classes phylogenetically distances: Unifrac family, including weighted, unweighted, generalized Unifrac, DPCoA which we introduce here. Through several lines evidence, a...

Monologic spoken discourse allows us to evaluate every day speech while retaining some experimental constraint. It also has clinical relevance, providing cognitive-linguistic information not measured on typical standardised tests. Here, we leverage big behavioural data (AphasiaBank) understand how genres (narrative, procedural, expositional), and unique tasks within those genres, influence microstructural elements of discourse. We compare task × microstructure interaction across speakers...

Abstract Somatic hypermutation (SHM) is the diversity-generating process in antibody affinity maturation. Probabilistic models of SHM are needed for analyzing rare mutations, understanding selective forces guiding maturation, and underlying biochemical process. High throughput data offers potential to develop fit on relevant sets. In this paper we model using modern frameworks. We motivated by recent work suggesting importance a wider context SHM, however, assigning an independent rate each...

Topic modeling is a popular method used to describe biological count data. With topic models, the user must specify number of topics $K$. Since there no definitive way choose $K$ and since true value might not exist, we develop method, which call alignment, study relationships across models with different In addition, present three diagnostics based on alignment. These techniques can show how many are consistently if only transiently present, or splits into more when increases. This strategy...

k -mer-based distances are often used to describe the differences between communities in metagenome sequencing studies because of their computational convenience and history effectiveness. Although do not use information about taxon abundances, we show that one class -mer metagenomes (the Euclidean distance spectra, or EKS distances) very closely related a phylogenetically-informed β -diversity measures explicitly both abundances phylogenetic relationships among taxa. Furthermore, these can...

When working with large biological data sets, exploratory analysis is an important first step for understanding the latent structure and generating hypotheses to be tested in subsequent analyses. However, when number of variables compared samples, standard methods such as principal components give results which are unstable difficult interpret. To mitigate these problems, we have developed a method allows analyst incorporate side information about relationships between way that encourages...

Exploratory analysis is an important first step for discovering latent structure and generating hypotheses in large biological data sets. However, when the number of variables compared to samples, standard methods such as principal components give results that are unstable difficult interpret. Here, we present adaptive generalized (adaptive gPCA), a new method solves these problems by incorporating information about relationships among variables. Adaptive gPCA gives low-dimensional...

The goal of dimension reduction tools is to construct a low-dimensional representation high-dimensional data. These are employed for variety reasons such as noise reduction, visualization, and lower computational costs. However, there fundamental issue that discussed in other modeling problems often overlooked reduction—overfitting. In the context problems, techniques feature-selection, cross-validation, regularization combat overfitting, but rarely precautions taken when applying reduction....

Topic modeling is a popular method used to describe biological count data. With topic models, the user must specify number of topics $K$. Since there no definitive way choose $K$ and since true value might not exist, we develop techniques study relationships across models with different This can show how many are consistently present if only transiently present, or splits in two when increases. strategy gives more insight into process generating data than choosing single would. We design...