New and emerging therapeutic options for malignant pleural mesothelioma: review of early clinical trials.

Malignant pleural mesothelioma (MPM) is a rare tumor that is challenging to control. Despite some benefit from using the multimodality-approach (surgery, combination chemotherapy and radiation), survival remains poor. However, current research produced a list of potential therapies. Here, we summarize significant new preclinical and early clinical developments in treatment of MPM, which include mesothelin specific antibody and toxin therapies, interleukin-4 (IL-4) receptor toxins, dendritic cell vaccines, immune checkpoint inhibitors, and gene-based therapies. In addition, several local modalities such as photodynamic therapy, postoperative lavage using betadine, and cryotherapy for local recurrence, have also shown to be effective for local control of disease

Immune Checkpoint Blockade and Adaptive Immune Resistance in Cancer

The clinical success of immune checkpoint blockers is a pivotal advancement for treating an increasing number of cancer types. However, immune checkpoint blockers still rarely induce complete remission and show little to no therapeutic efficacy in a significant percentage of cancer patients. Efforts are now underway to identify biomarkers that accurately predict which patients benefit from immune checkpoint blockers. Moreover, adaptive immune resistance can develop in tumors during treatment with immune checkpoint blockers. These adaptive resistance mechanisms in tumors might be disrupted by combining adjunctive immunotherapies, which could potentially improve the therapeutic efficacy of immune checkpoint blockers. This chapter discusses the mechanism of action of cytotoxic T lymphocyte antigen-4 (CTLA-4) and programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) immune checkpoint blockers and biomarkers that might predict clinical responses to these drugs. Lastly, ongoing research on mechanisms of tumor adaptive resistance could facilitate rationale design of adjunctive immunotherapies that can be synergistically combined with immune checkpoint blockers to more effectively treat cancer

Automatic estimation of flux distributions of astrophysical source populations

In astrophysics a common goal is to infer the flux distribution of populations of scientifically interesting objects such as pulsars or supernovae. In practice, inference for the flux distribution is often conducted using the cumulative distribution of the number of sources detected at a given sensitivity. The resulting "$\log(N>S)$-$\log (S)$" relationship can be used to compare and evaluate theoretical models for source populations and their evolution. Under restrictive assumptions the relationship should be linear. In practice, however, when simple theoretical models fail, it is common for astrophysicists to use prespecified piecewise linear models. This paper proposes a methodology for estimating both the number and locations of "breakpoints" in astrophysical source populations that extends beyond existing work in this field. An important component of the proposed methodology is a new interwoven EM algorithm that computes parameter estimates. It is shown that in simple settings such estimates are asymptotically consistent despite the complex nature of the parameter space. Through simulation studies it is demonstrated that the proposed methodology is capable of accurately detecting structural breaks in a variety of parameter configurations. This paper concludes with an application of our methodology to the Chandra Deep Field North (CDFN) data set.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS750 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Can education improve tax compliance? Evidence from different forms of tax education

We examine whether tax compliance is improved via different forms of tax education. We argue that different types of tax education have respective impacts on tax compliance. To explore this empirical issue, we conduct a survey related to tax compliance among 205 students taking either a general tax course or a technical tax course in Hong Kong. Our findings suggest that sales tax compliance among undergraduate students was significantly improved if they had been exposed to a general tax education, and income and sales tax compliance among postgraduate students were significantly improved if they had taken a technical tax course

Protective Heterologous Antiviral Immunity and Enhanced Immunopathogenesis Mediated by Memory T Cell Populations

A basic principle of immunology is that prior immunity results in complete protection against a homologous agent. In this study, we show that memory T cells specific to unrelated viruses may alter the host's primary immune response to a second virus. Studies with a panel of heterologous viruses, including lymphocytic choriomeningitis (LCMV), Pichinde (PV), vaccinia (VV), and murine cytomegalo (MCMV) viruses showed that prior immunity with one of these viruses in many cases enhanced clearance of a second unrelated virus early in infection. Such protective immunity was common, but it depended on the virus sequence and was not necessarily reciprocal. Cell transfer studies showed that both CD4 and CD8 T cell populations from LCMV-immune mice were required to transfer protective immunity to naive hosts challenged with PV or VV. In the case of LCMV-immune versus naive mice challenged with VV, there was an enhanced early recruitment of memory phenotype interferon (IFN) γ–secreting CD4+ and CD8+ cells into the peritoneal cavity and increased IFN-γ levels in this initial site of virus replication. Studies with IFN-γ receptor knockout mice confirmed a role for IFN-γ in mediating the protective effect by LCMV-immune T cell populations when mice were challenged with VV but not PV. In some virus sequences memory cell populations, although clearing the challenge virus more rapidly, elicited enhanced IFN-γ–dependent immunopathogenesis in the form of acute fatty necrosis. These results indicate that how a host responds to an infectious agent is a function of its history of previous infections and their influence on the memory T cell pool

A Frequentist Approach to Computer Model Calibration

This paper considers the computer model calibration problem and provides a general frequentist solution. Under the proposed framework, the data model is semi-parametric with a nonparametric discrepancy function which accounts for any discrepancy between the physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, this paper proposes a new and identifiable parametrization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates of convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. The practical performance of the proposed methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.Comment: 21 pages, 2 figure