Criminally Involved Parents Who Misuse Substances and Children’s Odds of Being Arrested as a Young Adult: Do Drug Treatment Courts Mitigate the Risk?

© 2016, Springer Science+Business Media New York.This paper examined (1) the association between parents who are convicted of a substance-related offense and their children’s probability of being arrested as a young adult and (2) whether or not parental participation in an adult drug treatment court program mitigated this risk. The analysis relied on state administrative data from North Carolina courts (2005–2013) and from birth records (1988–2003). The dependent variable was the probability that a child was arrested as a young adult (16–21). Logistic regression was used to compare groups and models accounted for the clustering of multiple children with the same mother. Findings revealed that children whose parents were convicted on either a substance-related charge on a non-substance-related charge had twice the odds of being arrested as young adult, relative to children whose parents had not been observed having a conviction. While a quarter of children whose parents participated in a drug treatment court program were arrested as young adults, parental completion this program did not reduce this risk. In conclusion, children whose parents were convicted had an increased risk of being arrested as young adults, irrespective of whether or not the conviction was on a substance-related charge. However, drug treatment courts did not reduce this risk. Reducing intergenerational links in the probability of arrest remains a societal challenge.

Association of HIV-1 Envelope-Specific Breast Milk IgA Responses with Reduced Risk of Postnatal Mother-to-Child Transmission of HIV-1.

UNLABELLED: Infants born to HIV-1-infected mothers in resource-limited areas where replacement feeding is unsafe and impractical are repeatedly exposed to HIV-1 throughout breastfeeding. Despite this, the majority of infants do not contract HIV-1 postnatally, even in the absence of maternal antiretroviral therapy. This suggests that immune factors in breast milk of HIV-1-infected mothers help to limit vertical transmission. We compared the HIV-1 envelope-specific breast milk and plasma antibody responses of clade C HIV-1-infected postnatally transmitting and nontransmitting mothers in the control arm of the Malawi-based Breastfeeding Antiretrovirals and Nutrition Study using multivariable logistic regression modeling. We found no association between milk or plasma neutralization activity, antibody-dependent cell-mediated cytotoxicity, or HIV-1 envelope-specific IgG responses and postnatal transmission risk. While the envelope-specific breast milk and plasma IgA responses also did not reach significance in predicting postnatal transmission risk in the primary model after correction for multiple comparisons, subsequent exploratory analysis using two distinct assay methodologies demonstrated that the magnitudes of breast milk total and secretory IgA responses against a consensus HIV-1 envelope gp140 (B.con env03) were associated with reduced postnatal transmission risk. These results suggest a protective role for mucosal HIV-1 envelope-specific IgA responses in the context of postnatal virus transmission. This finding supports further investigations into the mechanisms by which mucosal IgA reduces risk of HIV-1 transmission via breast milk and into immune interventions aimed at enhancing this response. IMPORTANCE: Infants born to HIV-1-infected mothers are repeatedly exposed to the virus in breast milk. Remarkably, the transmission rate is low, suggesting that immune factors in the breast milk of HIV-1-infected mothers help to limit transmission. We compared the antibody responses in plasma and breast milk of HIV-1-transmitting and -nontransmitting mothers to identify responses that correlated with reduced risk of postnatal HIV-1 transmission. We found that neither plasma nor breast milk IgG antibody responses were associated with risk of HIV-1 transmission. In contrast, the magnitudes of the breast milk IgA and secretory IgA responses against HIV-1 envelope proteins were associated with reduced risk of postnatal HIV-1 transmission. The results of this study support further investigations of the mechanisms by which mucosal IgA may reduce the risk of HIV-1 transmission via breastfeeding and the development of strategies to enhance milk envelope-specific IgA responses to reduce mother-to-child HIV transmission and promote an HIV-free generation.

Structural and Functional Analysis of the Caspase –dependent and –independent Domains of the X-linked Inhibitor of Apoptosis Protein in Inflammatory Breast Cancer Tumor Biology

Inflammatory breast cancer (IBC) is an extremely rare but highly aggressive form of breast cancer characterized by the rapid development of therapeutic resistance leading to particularly poor survival. Our previous work focused on the elucidation of factors that mediate therapeutic resistance in IBC and identified increased expression of the anti-apoptotic protein, X-linked inhibitor of apoptosis protein (XIAP), to correlate with the development of resistance to chemotherapeutics. Although XIAP is classically thought of as an inhibitor of caspase activation, multiple studies have revealed that XIAP can also function as a signaling intermediate in numerous pathways. Based on preliminary evidence revealing high expression of XIAP in pre-treatment IBC cells rather than only subsequent to the development of resistance, we hypothesized that XIAP could play an important signaling role in IBC pathobiology outside of its heavily published apoptotic inhibition function. Further, based on our discovery of inhibition of chemotherapeutic efficacy, we postulated that XIAP overexpression might also play a role in resistance to other forms of therapy, such as immunotherapy. Finally, we posited that targeting of specific redox adaptive mechanisms, which are observed to be a significant barrier to successful treatment of IBC, could overcome therapeutic resistance and enhance the efficacy of chemo-, radio-, and immuno- therapies. To address these hypotheses our objectives were: 1. to determine a role for XIAP in IBC pathobiology and to elucidate the upstream regulators and downstream effectors of XIAP; 2. to evaluate and describe a role for XIAP in the inhibition of immunotherapy; and 3. to develop and characterize novel redox modulatory strategies that target identified mechanisms to prevent or reverse therapeutic resistance.

Using various genomic and proteomic approaches, combined with analysis of cellular viability, proliferation, and growth parameters both in vitro and in vivo, we demonstrate that XIAP plays a central role in both IBC pathobiology in a manner mostly independent of its role as a caspase-binding protein. Modulation of XIAP expression in cells derived from patients prior to any therapeutic intervention significantly altered key aspects IBC biology including, but not limited to: IBC-specific gene signatures; the tumorigenic capacity of tumor cells; and the metastatic phenotype of IBC, all of which are revealed to functionally hinge on XIAP-mediated NFκB activation, a robust molecular determinant of IBC. Identification of the mechanism of XIAP-mediated NFκB activation led to the characterization of novel peptide-based antagonist which was further used to identify that increased NFκB activation was responsible for redox adaptation previously observed in therapy-resistant IBC cells. Lastly, we describe the targeting of this XIAP-NFκB-ROS axis using a novel redox modulatory strategy both in vitro and in vivo. Together, the data presented here characterize a novel and crucial role for XIAP both in therapeutic resistance and the pathobiology of IBC; these results confirm our previous work in acquired therapeutic resistance and establish the feasibility of targeting XIAP-NFκB and the redox adaptive phenotype of IBC as a means to enhance survival of patients.

Why Serological Responses during Cystitis are Limited.

The high frequency of urinary tract infections (UTIs), some of which appear to be endogenous relapses rather than reinfections by new isolates, point to defects in the host's memory immune response. It has been known for many decades that, whereas kidney infections evoked an antibody response to the infecting bacteria, infections limited to the bladder failed to do so. We have identified the existence of a broadly immunosuppressive transcriptional program associated with the bladder, but not the kidneys, during infection of the urinary tract that is dependent on bladder mast cells. This involves the localized secretion of IL-10 and results in the suppression of humoral immune responses in the bladder. Mast cell-mediated immune suppression could suggest a role for these cells in critically balancing the needs to clear infections with the imperative to prevent harmful immune reactions in the host.

IL-10-producing Regulatory B Cell Development in Human Autoimmune Disease

B cell abnormalities contribute to the development and progress of autoimmune disease. Traditionally, the role of B cells in autoimmune disease was thought to be predominantly limited to the production of autoantibodies. Nevertheless, in addition to autoantibody production, B cells have other functions potentially relevant to autoimmunity. Such functions include antigen presentation to and activation of T cells, expression of costimulatory molecules and cytokine production. Recently, the ability of B cells to negatively regulate cellular immune responses and inflammation has been described and the concept of “regulatory B cells” has emerged. A variety of cytokines produced by regulatory B cell subsets have been reported with interleukin-10 (IL-10) being the most studied. IL-10-producing regulatory B cells predominantly localize within a rare CD1dhiCD5+ B cell subset in mice and the CD24hiCD27+ B cell subset in adult humans. This specific IL-10-producing subset of regulatory B cells have been named “B10 cells” to highlight that the regulatory function of these rare B cells is primarily mediated by IL-10, and to distinguish them from other regulatory B cell subsets that regulate immune responses through different mechanisms. B10 cells have been studies in a variety of animal models with autoimmune disease and clinical settings of human autoimmunity. There are many unsolved questions related to B10 cells including their surface phenotype, their origin and development in vivo, and their role in autoimmunity.

In Chapter 3 of this dissertation, the role of the B cell receptor (BCR) in B10 cell development is highlighted. First, the BCR repertoire of mouse peritoneal cavity B10 cells is examined by single cell sequencing; peritoneal cavity B10 cells have clonally diverse germline BCRs that are predominantly unmutated. Second, mouse B10 cells are shown to have higher frequencies of λ+ BCRs compared to non-B10 cells which may indicate the involvement of BCR light chain editing early in the process of B10 cell development in vivo. Third, human peripheral blood B10 cells are examined and are also found to express higher frequencies of λ chains compared to non-b10 cells. Therefore, B10 cell BCRs are clonally diverse and enriched for unmutated germline sequences and λ light chains.

In Chapter 4 of this dissertation, B10 cells are examined in the healthy developing human across the entire age range of infancy, childhood and adolescence, and in a large cohort of children with autoimmunity. The study of B10 cells in the developing human documents a massive transient expansion during middle childhood when up to 30% of blood B cells were competent to produce IL-10. The surface phenotype of pediatric B10 cells was variable and reflective of overall B cell development. B10 cells down-regulated CD4+ T cell interferon-gamma (IFN-γ) production through IL-10-dependent pathways and IFN-γ inhibited whereas interleukin-21 (IL-21) promoted B cell IL-10 competency in vitro. Children with autoimmunity had a contracted B10 cell compartment, along with increased IFN-γ and decreased IL-21 serum levels compared to age-matched healthy controls. The decreased B10 cell frequencies and numbers in children with autoimmunity may be partially explained by the differential regulation of B10 cell development by IFN-γ and IL-21 and alterations in serum cytokine levels. The age-related changes of the B10 cell compartment during normal human development provide new insights into immune tolerance mechanisms involved in inflammation and autoimmunity.

These studies collectively demonstrate that BCR signals are the most important early determinant of B10 cell development in vivo, that human B10 cells are not a surface phenotype defined developmental B cell subset but a functionally defined regulatory B cell subset that regulates CD4+ T IFN-γ production through IL-10-dependent pathways and that human B10 cell development can be regulated by soluble factors in vivo such as the cytokine milieu. The findings of these studies provide new insights into immune tolerance mechanisms involved in human autoimmunity and the potent effects of IL-21 on human B cell IL-10 competence in vitro open new horizons in the development of autologous B10 cell-based therapies as an approach to treat human autoimmune disease in the future.

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.