The Intratumor Bacterial and Fungal Microbiome Is Characterized by HPV,Smoking, and Alcohol Consumption in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) tumor phenotypes and clinical outcomes are significantly influenced by etiological agents, such as HPV infection, smoking, and alcohol consumption. Accordingly, the intratumor microbiome has been increasingly implicated in cancer progression and metastasis. However, few studies characterize the intratumor microbial landscape of HNSCC with respect to these etiological agents. In this study, we aimed to investigate the bacterial and fungal landscape of HNSCC in association with HPV infection, smoking, and alcohol consumption. RNA-sequencing data were extracted from The Cancer Genome Atlas (TCGA) regarding 449 tissue samples and 44 normal samples. Pathoscope 2.0 was used to extract the microbial reads. Microbe abundance was compared to clinical variables, oncogenic signatures, and immune-associated pathways. Our results demonstrated that a similar number of dysregulated microbes was overabundant in smokers and nonsmokers, while heavy drinkers were characterized by an underabundance of dysregulated microbes. Conversely, the majority of dysregulated microbes were overabundant in HPV+ tumor samples when compared to HPV- tumor samples. Moreover, we observed that many dysregulated microbes were associated with oncogenic and metastatic pathways, suggesting their roles in influencing carcinogenesis. These microbes provide insights regarding potential mechanisms for tumor pathogenesis and progression with respect to the three etiological agents.     

Computationally efficient framework for diagnosing,understanding and predicting biphasic population growth

Throughout the life sciences, biological populations undergo multiple phases of growth, often referred to as biphasic growth for the commonly encountered situation involving two phases. Biphasic population growth occurs over a massive range of spatial and temporal scales, ranging from microscopic growth of tumours over several days, to decades-long regrowth of corals in coral reefs that can extend for hundreds of kilometres. Different mathematical models and statistical methods are used to diagnose, understand and predict biphasic growth. Common approaches can lead to inaccurate predictions of future growth that may result in inappropriate management and intervention strategies being implemented. Here, we develop a very general computationally efficient framework, based on profile likelihood analysis, for diagnosing, understanding and predicting biphasic population growth. The two key components of the framework are as follows: (i) an efficient method to form approximate confidence intervals for the change point of the growth dynamics and model parameters and (ii) parameter-wise profile predictions that systematically reveal the influence of individual model parameters on predictions. To illustrate our framework we explore real-world case studies across the life sciences.     

Tumor-Localized Administration of α-GalCer to Recruit Invariant Natural Killer T Cells and Enhance Their Antitumor Activity against Solid Tumors

Invariant natural killer T (iNKT) cells have the capacity to mount potent anti-tumor reactivity and have therefore become a focus in the development of cell-based immunotherapy. iNKT cells attack tumor cells using multiple mechanisms with a high efficacy; however, their clinical application has been limited because of their low numbers in cancer patients and difficulties in infiltrating solid tumors. In this study, we aimed to overcome these critical limitations by using α-GalCer, a synthetic glycolipid ligand specifically activating iNKT cells, to recruit iNKT to solid tumors. By adoptively transferring human iNKT cells into tumor-bearing humanized NSG mice and administering a single dose of tumor-localized α-GalCer, we demonstrated the rapid recruitment of human iNKT cells into solid tumors in as little as one day and a significantly enhanced tumor killing ability. Using firefly luciferase-labeled iNKT cells, we monitored the tissue biodistribution and pharmacokinetics/pharmacodynamics (PK/PD) of human iNKT cells in tumor-bearing NSG mice. Collectively, these preclinical studies demonstrate the promise of an αGC-driven iNKT cell-based immunotherapy to target solid tumors with higher efficacy and precision.     

Slicing Software for Model Construction

Applying finite-state verification techniques (e.g., model checking) to software requires that program source code be translated to a finite-state transition system that safely models program behavior. Automatically checking such a transition system for a correctness property is typically very costly, thus it is necessary to reduce the size of the transition system as much as possible. In fact, it is often the case that much of a program's source code is irrelevant for verifying a given correctness property.In this paper, we apply program slicing techniques to remove automatically such irrelevant code and thus reduce the size of the corresponding transition system models. We give a simple extension of the classical slicing definition, and prove its safety with respect to model checking of linear temporal logic (LTL) formulae. We discuss how this slicing strategy fits into a general methodology for deriving effective software models using abstraction-based program specialization.     

Psychological impact of benign breast biopsy: A longitudinal, comparative study.

The impact of benign breast biopsy (BBB) on distress and perceptions of risk for breast cancer (BC) was examined. Interviews were conducted with 100 women shortly after notification of biopsy results and 4 and 8 months post-BBB. Compared with matched healthy comparison (HC) women without BBB, the BBB group evidenced greater BC-specific distress at baseline. BC-specific distress declined after BBB, remaining elevated relative to the HC group at the 8-month follow-up. Dispositional (optimism, informational coping style), demographic (education), clinical (family history of BC), and cognitive (BC risk perception) variables were associated with baseline levels of BC-specific distress or persistence of distress. Results support the monitoring process model (S. M. Miller, 1995) and the cognitive social health information processing model (S. M. Miller, Y. Shoda, & K. Hurley, 1996). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nonlinear control techniques for an atomic force microscope system

Two nonlinear control techniques are proposed for an atomic force microscope system. Initially, a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically, the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Simulation results are provided to illttstrate the efficacy and performance of the control strategies.     

Analysis of input-to-state stability for discrete time nonlinear systems via dynamic programming

The input-to-state stability (ISS) property for systems with disturbances has received considerable attention over the past decade or so, with many applications and characterizations reported in the literature. The main purpose of this paper is to present analysis results for ISS that utilize dynamic programming techniques to characterize minimal ISS gains and transient bounds. These characterizations naturally lead to computable necessary and sufficient conditions for ISS. Our results make a connection between ISS and optimization problems in nonlinear dissipative systems theory (including L₂-gain analysis and nonlinear H_∞ theory). As such, the results presented address an obvious gap in the literature.     

The Synchronous Approach to Designing Reactive Systems

Synchronous programming is available through several formally defined languages having very different characteristics: Esterel is imperative, while Lustre and Signal are declarative in style; Statecharts and Argos are graphical languages that allow one to program by constructing hierarchical automata. Our motivation for taking the synchronous design paradigm further, integrating imperative, declarative (or dataflow), and graphical programming styles, is that real systems typically have components that match each of these profiles. This paper motivates our interest in the mixed language programming of embedded software around a number of examples, and sketches the semantical foundation of the Synchronie toolset which ensures a coherent computational model. This toolset supports a design trajectory that incorporates rapid prototyping and systematic testing for early design validation, an object oriented development methodology for long term software management, and formal verification at the level of automatically generated object code.     

Multistaged Anaerobic Sludge Digestion Processes

Two multistaged anaerobic digestion systems, a four-stage thermophilic anaerobic digestion (4TAD), all at 55°C, and a four-stage anaerobic digestion with a tapered temperature configuration (4ADT) at 55, 49, 43, and 37°C, respectively, were studied to evaluate their solids, volatile organic sulfur compounds, and indicator organism (E. coli and fecal coliform) reduction potentials. The 4TAD system removed significantly more volatile solids from sludges than the 4ADT system (6%). However, the dewatered biosolids cakes from the 4ADT system generated fewer organic sulfur compounds than those from the 4TAD system. Both multistage systems showed better digestion efficiencies than single-stage mesophilic or single-stage thermophilic anaerobic digesters at the same overall retention time. However, the lowest organic sulfur compounds were observed from the single mesophilic system. Both multistage anaerobic digestion systems failed to dramatically remove DNA of the indicator organism, E. coli, quantified by real time polymerase chain reaction, even though the indicator organism densities measured by standard culturing methods satisfied EPA Class A biosolids requirements.     

Comparison of opportunities to respond within a drill model when rehearsing sight words with a child with mental retardation.

Sight-word instruction can improve functioning with various daily, recreational, and work-related tasks among children with moderate to severe disabilities. Previous research has demonstrated the effectiveness of drill methods to teach sight words if the model contains at least 50% known items, which would also increase the number of opportunities to respond (OTR) to the target item. The current study taught five sight words each day to a child diagnosed as moderately mentally retarded using high OTR and moderate OTR conditions and a drill ratio of 10% unknown to 90% known. Results suggested that the high OTR condition led to better retention than the moderate OTR despite containing an equal ratio of unknown to known items between them. Implications for practicing school psychologists and future research are included. (PsycINFO Database Record (c) 2010 APA, all rights reserved)