Nonparametric clustering for spatio-temporal data

Clustering algorithms attempt the identification of distinct subgroups within heterogeneous data and are commonly utilised as an exploratory tool. The definition of a cluster is dependent on the relevant dataset and associated constraints; clustering methods seek to determine homogeneous subgroups that each correspond to a distinct set of characteristics. This thesis focuses on the development of spatial clustering algorithms and the methods are motivated by the complexities posed by spatio-temporal data. The examples in this thesis primarily come from spatial structures described in the context of traffic modelling and are based on occupancy observations recorded over time for an urban road network. Levels of occupancy indicate the extent of traffic congestion and the goal is to identify distinct regions of traffic congestion in the urban road network. Spatial clustering for spatio-temporal data is an increasingly important research problem and the challenges posed by such research problems often demand the development of bespoke clustering methods. Many existing clustering algorithms, with a focus on accommodating the underlying spatial structure, do not generate clusters that adequately represent differences in the temporal pattern across the network. This thesis is primarily concerned with developing nonparametric clustering algorithms that seek to identify spatially contiguous clusters and retain underlying temporal patterns. Broadly, this thesis introduces two clustering algorithms that are capable of accommodating spatial and temporal dependencies that are inherent to the dataset. The first is a functional distributional clustering algorithm that is implemented within an agglomerative hierarchical clustering framework as a two-stage process. The method is based on a measure of distance that utilises estimated cumulative distribution functions over the data and this unique distance is both functional and distributional. This notion of distance utilises the differences in densities to identify distinct clusters in the graph, rather than raw recorded observations. However, distinct characteristics may not necessarily be identified and distinguishable by a densities-based distance measure, as defined within the agglomerative hierarchical clustering framework. In this thesis, we also introduce a formal Bayesian clustering approach that enables the researcher to determine spatially contiguous clusters in a data-driven manner. This framework varies from the set of assumptions introduced by the functional distributional clustering algorithm. This flexible Bayesian model employs a binary dependent Chinese restaurant process (binDCRP) to place a prior over the geographical constraints posed by a graph-based network. The binDCRP is a special case of the distance dependent Chinese restaurant process that was first introduced by Blei and Frazier (2011); the binDCRP is modified to account for data that poses spatial constraints. The binDCRP seeks to cluster data such that adjacent or neighbouring regions in a spatial structure are more likely to belong to the same cluster. The binDCRP introduces a large number of singletons within the spatial structure and we modify the binDCRP to enable the researcher to restrict the number of clusters in the graph. It is also reasonable to assume that individual junctions within a cluster are spatially correlated to adjacent junctions, due to the nature of traffic and the spread of congestion. In order to fully account for spatial correlation within a cluster structure, the model utilises a type of the conditional auto-regressive (CAR) model. The model also accounts for temporal dependencies using a first order auto-regressive (AR-1) model. In this mean-based flexible Bayesian model, the data is assumed to follow a Gaussian distribution and we utilise Kronecker product identities within the definition of the spatio-temporal precision matrix to improve the computational efficiency. The model utilises a Metropolis within Gibbs sampler to fully explore all possible partition structures within the network and infer the relevant parameters of the spatio-temporal precision matrix. The flexible Bayesian method is also applicable to map-based spatial structures and we describe the model in this context as well. The developed Bayesian model is applied to a simulated spatio-temporal dataset that is composed of three distinct known clusters. The differences in the clusters are reflected by distinct mean values over time associated with spatial regions. The nature of this mean-based comparison differs from the functional distributional clustering approach that seeks to identify differences across the distribution. We demonstrate the ability of the Bayesian model to restrict the number of clusters using a simulated data structure with distinctly defined clusters. The sampler is also able to explore potential cluster structures in an efficient manner and this is demonstrated using a simulated spatio-temporal data structure. The performance of this model is illustrated by an application to a dataset over an urban road network that presents traffic as a process varying continuously across space and time. We also apply this model to an areal unit dataset composed of property prices over a period of time for the Avon county in England

Type I interferons act directly on CD8 T cells to allow clonal expansion and memory formation in response to viral infection

T cell expansion and memory formation are generally more effective when elicited by live organisms than by inactivated vaccines. Elucidation of the underlying mechanisms is important for vaccination and therapeutic strategies. We show that the massive expansion of antigen-specific CD8 T cells that occurs in response to viral infection is critically dependent on the direct action of type I interferons (IFN-Is) on CD8 T cells. By examining the response to infection with lymphocytic choriomeningitis virus using IFN-I receptor–deficient (IFN-IR0) and –sufficient CD8 T cells adoptively transferred into normal IFN-IR wild-type hosts, we show that the lack of direct CD8 T cell contact with IFN-I causes >99% reduction in their capacity to expand and generate memory cells. The diminished expansion of IFN-IR0 CD8 T cells was not caused by a defect in proliferation but by poor survival during the antigen-driven proliferation phase. Thus, IFN-IR signaling in CD8 T cells is critical for the generation of effector and memory cells in response to viral infection

IL-15 trans-presentation by pulmonary dendritic cells promotes effector CD8 T cell survival during influenza virus infection

We have recently demonstrated that peripheral CD8 T cells require two separate activation hits to accumulate to high numbers in the lungs after influenza virus infection: a primary interaction with mature, antigen-bearing dendritic cells (DCs) in the lymph node, and a second, previously unrecognized interaction with MHC I–viral antigen–bearing pulmonary DCs in the lungs. We demonstrate that in the absence of lung-resident DC subsets, virus-specific CD8 T cells undergo significantly increased levels of apoptosis in the lungs; however, reconstitution with pulmonary plasmacytoid DCs and CD8α+ DCs promotes increased T cell survival and accumulation in the lungs. Further, our results show that the absence of DCs after influenza virus infection results in significantly reduced levels of IL-15 in the lungs and that pulmonary DC–mediated rescue of virus-specific CD8 T cell responses in the lungs requires trans-presentation of IL-15 via DC-expressed IL-15Rα. This study demonstrates a key, novel requirement for DC trans-presented IL-15 in promoting effector CD8 T cell survival in the respiratory tract after virus infection, and suggests that this trans-presentation could be an important target for the development of unique antiviral therapies and more effective vaccine strategies

Mitochondrial CoQ deficiency is a common driver of mitochondrial oxidants and insulin resistance.

Insulin resistance in muscle, adipocytes and liver is a gateway to a number of metabolic diseases. Here, we show a selective deficiency in mitochondrial coenzyme Q (CoQ) in insulin-resistant adipose and muscle tissue. This defect was observed in a range of in vitro insulin resistance models and adipose tissue from insulin-resistant humans and was concomitant with lower expression of mevalonate/CoQ biosynthesis pathway proteins in most models. Pharmacologic or genetic manipulations that decreased mitochondrial CoQ triggered mitochondrial oxidants and insulin resistance while CoQ supplementation in either insulin-resistant cell models or mice restored normal insulin sensitivity. Specifically, lowering of mitochondrial CoQ caused insulin resistance in adipocytes as a result of increased superoxide/hydrogen peroxide production via complex II. These data suggest that mitochondrial CoQ is a proximal driver of mitochondrial oxidants and insulin resistance, and that mechanisms that restore mitochondrial CoQ may be effective therapeutic targets for treating insulin resistance

Mitochondrial CoQ deficiency is a common driver of mitochondrial oxidants and insulin resistance

Insulin resistance in muscle, adipocytes and liver is a gateway to a number of metabolic diseases. Here, we show a selective deficiency in mitochondrial coenzyme Q (CoQ) in insulin-resistant adipose and muscle tissue. This defect was observed in a range of in vitro insulin resistance models and adipose tissue from insulin-resistant humans and was concomitant with lower expression of mevalonate/CoQ biosynthesis pathway proteins in most models. Pharmacologic or genetic manipulations that decreased mitochondrial CoQ triggered mitochondrial oxidants and insulin resistance while CoQ supplementation in either insulin-resistant cell models or mice restored normal insulin sensitivity. Specifically, lowering of mitochondrial CoQ caused insulin resistance in adipocytes as a result of increased superoxide/hydrogen peroxide production via complex II. These data suggest that mitochondrial CoQ is a proximal driver of mitochondrial oxidants and insulin resistance, and that mechanisms that restore mitochondrial CoQ may be effective therapeutic targets for treating insulin resistance

Down-Regulation of the Interferon Signaling Pathway in T Lymphocytes from Patients with Metastatic Melanoma

BACKGROUND: Dysfunction of the immune system has been documented in many types of cancers. The precise nature and molecular basis of immune dysfunction in the cancer state are not well defined. METHODS AND FINDINGS: To gain insights into the molecular mechanisms of immune dysfunction in cancer, gene expression profiles of pure sorted peripheral blood lymphocytes from 12 patients with melanoma were compared to 12 healthy controls. Of 25 significantly altered genes in T cells and B cells from melanoma patients, 17 are interferon (IFN)-stimulated genes. These microarray findings were further confirmed by quantitative PCR and functional responses to IFNs. The median percentage of lymphocytes that phosphorylate STAT1 in response to interferon-α was significantly reduced (Δ = 16.8%; 95% confidence interval, 0.98% to 33.35%) in melanoma patients (n = 9) compared to healthy controls (n = 9) in Phosflow analysis. The Phosflow results also identified two subgroups of patients with melanoma: IFN-responsive (33%) and low-IFN-response (66%). The defect in IFN signaling in the melanoma patient group as a whole was partially overcome at the level of expression of IFN-stimulated genes by prolonged stimulation with the high concentration of IFN-α that is achievable only in IFN therapy used in melanoma. The lowest responders to IFN-α in the Phosflow assay also showed the lowest gene expression in response to IFN-α. Finally, T cells from low-IFN-response patients exhibited functional abnormalities, including decreased expression of activation markers CD69, CD25, and CD71; T(H)1 cytokines interleukin-2, IFN-γ, and tumor necrosis factor α, and reduced survival following stimulation with anti-CD3/CD28 antibodies compared to controls. CONCLUSIONS: Defects in interferon signaling represent novel, dominant mechanisms of immune dysfunction in cancer. These findings may be used to design therapies to counteract immune dysfunction in melanoma and to improve cancer immunotherapy

Temporal Regulation of Rapamycin on Memory CTL Programming by IL-12

Mammalian target of rapamycin (mTOR) is a master regulator of cell growth. Recent reports have defined its important role in memory cytotoxic T lymphocyte (CTL) differentiation in infections and memory programming. We report that rapamycin regulated memory CTL programming by IL-12 to a similar level in a wide range of concentrations, and the enhanced memory CTLs by rapamycin were functional and provided similar protection against Listeria Monocytogenes challenge compared to the control. In addition, rapamycin-experienced CTLs went through substantially enhanced proliferation after transfer into recipients. Furthermore, the regulatory function of rapamycin on CD62L expression in memory CTLs was mainly contributed by the presence of rapamycin in the first 24-hr of stimulation in vitro, whereas the effective window of rapamycin on the size of memory CTLs was determined between 24 to 72 hrs. In conclusion, rapamycin regulates IL-12-driven programming of CTLs to a similar level in a wide range of concentrations, and regulates the phenotype and the size of memory CTLs in different temporal windows

In Vivo Depletion of Lymphotoxin-Alpha Expressing Lymphocytes Inhibits Xenogeneic Graft-versus-Host-Disease

Graft-versus-host disease (GVHD) is a major barrier to successful allogeneic hematopoietic cell transplantation and is largely mediated by activated donor lymphocytes. Lymphotoxin (LT)-α is expressed by subsets of activated T and B cells, and studies in preclinical models demonstrated that targeted depletion of these cells with a mouse anti-LT-α monoclonal antibody (mAb) was efficacious in inhibiting inflammation and autoimmune disease. Here we demonstrate that LT-α is also upregulated on activated human donor lymphocytes in a xenogeneic model of GVHD and targeted depletion of these donor cells ameliorated GVHD. A depleting humanized anti-LT-α mAb, designated MLTA3698A, was generated that specifically binds to LT-α in both the soluble and membrane-bound forms, and elicits antibody-dependent cellular cytotoxicity (ADCC) activity in vitro. Using a human peripheral blood mononuclear cell transplanted SCID (Hu-SCID) mouse model of GVHD, the anti-human LT-α mAb specifically depleted activated LT-expressing human donor T and B cells, resulting in prolonged survival of the mice. A mutation in the Fc region, rendering the mAb incapable of mediating ADCC, abolished all in vitro and in vivo effects. These data support a role for using a depleting anti-LT-α antibody in treating immune diseases such as GVHD and autoimmune diseases

Direct Type I IFN but Not MDA5/TLR3 Activation of Dendritic Cells Is Required for Maturation and Metabolic Shift to Glycolysis after Poly IC Stimulation

We thank the Rockefeller University Center for Clinical and Translational Science (UL1 TR000043 NCATS, NIH) for technical support

Inflammatory chemokine receptors regulate CD8+ T cell contraction and memory generation following infection

CD8+ T cells lacking CXCR3 and CCR5 expression have impaired contraction and generate an increased number of memory cells after virus infection