Bruton's Tyrosine Kinase (BTK) and IL-2 Inducible T-cell Kinase (ITK) are enzymes responsible for the phosphorylation and activation of downstream effectors in the B-cell receptor (BCR) signaling and ...T cell receptor (TCR) signaling pathways, respectively. Ibrutinib is an FDA-approved potent inhibitor of both BTK and ITK that impairs B-cell and T-cell function. CD4 T cells and B cells are essential for the induction of chronic graft-versus-host disease (cGVHD). We evaluated these targets by testing the ability of Ibrutinib to prevent or ameliorate cGVHD, which is one of the major complications for patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). We found that Ibrutinib significantly alleviated cGVHD across four different mouse models, accompanied by increased long-term survival and reduced clinical score. The clinical improvements in Ibrutinib-treated recipients were associated with decreased serum-autoantibodies, costimulatory molecule activation, B-cell proliferation, and glomerulonephritis compared to vehicle controls. Ibrutinib was also able to alleviate the clinical manifestations in acute GVHD (aGVHD), where the recipients were given grafts with or without B cells, suggesting that an inhibitory effect of Ibrutinib on T cells contributes to a reduction in both aGVHD and cGVHD pathogenesis. An effective prophylactic regimen is still lacking to both reduce the incidence and severity of human cGVHD following allo-HSCT. Our study shows that Ibrutinib is an effective prophylaxis against several mouse models of cGVHD with minimal toxicity and could be a promising strategy to combat human cGVHD clinically.
To understand the transmissibility and spread of infectious diseases, epidemiologists turn to estimates of the instantaneous reproduction number. While many estimation approaches exist, their utility ...may be limited. Challenges of surveillance data collection, model assumptions that are unverifiable with data alone, and computationally inefficient frameworks are critical limitations for many existing approaches. We propose a discrete spline-based approach that solves a convex optimization problem—Poisson trend filtering—using the proximal Newton method. It produces a locally adaptive estimator for instantaneous reproduction number estimation with heterogeneous smoothness. Our methodology remains accurate even under some process misspecifications and is computationally efficient, even for large-scale data. The implementation is easily accessible in a lightweight R package rtestim .
Personal data for 108 individuals were collected during a 9-month period, including whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points; and daily ...activity tracking. Using all of these data, we generated a correlation network that revealed communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). We calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). Finally, behavioral coaching informed by personal data helped participants to improve clinical biomarkers. Our results show that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states.
The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The ...National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.
The Netflix Effect Kevin McDonald, Daniel Smith-Rowsey / Kevin McDonald, Daniel Smith-Rowsey
2016, 2016-08-11
eBook
Netflix is the definitive media company of the 21st century. It was among the first to parlay new Internet technologies into a successful business model, and in the process it changed how consumers ...access film and television. It is now one of the leading providers of digitally delivered media content and is continually expanding access across a host of platforms and mobile devices. Despite its transformative role, however, Netflix has drawn very little critical attention-far less than competitors such as YouTube, Apple, Amazon, Comcast, and HBO. This collection addresses this gap, as the essays are designed to critically explore the breadth and diversity of Netflix's effect from a variety of different scholarly perspectives, a necessary approach considering the hybrid nature of Netflix, its inextricable links to new models of media production, distribution, viewer engagement and consumer behavior, its relationship to existing media conglomerates and consumer electronics, its capabilities as a web-based service provider and data network, and its reliance on a broader technological infrastructure.
Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here ...we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
The Microbiome and Human Biology Knight, Rob; Callewaert, Chris; Marotz, Clarisse ...
Annual review of genomics and human genetics,
08/2017, Letnik:
18, Številka:
1
Journal Article
Recenzirano
Over the past few years, microbiome research has dramatically reshaped our understanding of human biology. New insights range from an enhanced understanding of how microbes mediate digestion and ...disease processes (e.g., in inflammatory bowel disease) to surprising associations with Parkinson's disease, autism, and depression. In this review, we describe how new generations of sequencing technology, analytical advances coupled to new software capabilities, and the integration of animal model data have led to these new discoveries. We also discuss the prospects for integrating studies of the microbiome, metabolome, and immune system, with the goal of elucidating mechanisms that govern their interactions. This systems-level understanding will change how we think about ourselves as organisms.
•Projection scrubbing is a data-driven, statistically principled scrubbing method for fMRI based on ICA or other projections.•Data-driven scrubbing produces more valid, reliable, and identifiable FC ...on average, compared with motion scrubbing.•Data-driven scrubbing avoids unnecessary censoring by only flagging volumes that display abnormal patterns.•Data-driven scrubbing dramatically increases sample size by avoiding high rates of subject exclusion.
Functional MRI (fMRI) data may be contaminated by artifacts arising from a myriad of sources, including subject head motion, respiration, heartbeat, scanner drift, and thermal noise. These artifacts cause deviations from common distributional assumptions, introduce spatial and temporal outliers, and reduce the signal-to-noise ratio of the data—all of which can have negative consequences for the accuracy and power of downstream statistical analysis. Scrubbing is a technique for excluding fMRI volumes thought to be contaminated by artifacts and generally comes in two flavors. Motion scrubbing based on subject head motion-derived measures is popular but suffers from a number of drawbacks, among them the need to choose a threshold, a lack of generalizability to multiband acquisitions, and high rates of censoring of individual volumes and entire subjects. Alternatively, data-driven scrubbing methods like DVARS are based on observed noise in the processed fMRI timeseries and may avoid some of these issues. Here we propose “projection scrubbing”, a novel data-driven scrubbing method based on a statistical outlier detection framework and strategic dimension reduction, including independent component analysis (ICA), to isolate artifactual variation. We undertake a comprehensive comparison of motion scrubbing with data-driven projection scrubbing and DVARS. We argue that an appropriate metric for the success of scrubbing is maximal data retention subject to reasonable performance on typical benchmarks such as the validity, reliability, and identifiability of functional connectivity. We find that stringent motion scrubbing yields worsened validity, worsened reliability, and produced small improvements to fingerprinting. Meanwhile, data-driven scrubbing methods tend to yield greater improvements to fingerprinting while not generally worsening validity or reliability. Importantly, however, data-driven scrubbing excludes a fraction of the number of volumes or entire sessions compared to motion scrubbing. The ability of data-driven fMRI scrubbing to improve data retention without negatively impacting the quality of downstream analysis has major implications for sample sizes in population neuroscience research.
Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these ...techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.
Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression
. Diagnostic applications have been proposed for ...inflammatory bowel disease diagnosis and prognosis
, colorectal cancer prescreening
and therapeutic choices in melanoma
. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic
and cardiovascular diseases
. To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks.
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