A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient''s disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [¹⁸F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.     

Classification of shoreline vegetation in the Western Basin of Lake Erie using airborne hyperspectral imager HSI2, Pleiades and UAV data

Mapping land and aquatic vegetation of coastal areas using remote sensing for better management and conservation has been a long-standing interest in many parts of the world. Due to natural complexity and heterogeneity of vegetation cover, various remote sensing sensors and techniques are utilized for monitoring coastal ecosystems. In this study, two unsupervised and two supervised standard pixel-based classifiers were tested to evaluate the mapping performance of the second-generation airborne NASA Glenn Hyperspectral Imager (HSI2) over the narrow coastal area along the Western Lake Erie’s shoreline. Furthermore, the classification results of HSI2 (using the whole Visible-Near Infrared (VIS+ NIR) hyperspectral dataset, and also the spectral subset of Visible (VIS) spectral bands) were compared to multispectral Pleiades (VIS+ NIR) and Unmanned Aerial Vehicle (UAV) VIS classified images. The goal was to explore how different spectral ranges, and spatial and spectral resolutions impact the unsupervised and supervised classifiers. While the unsupervised classifiers depended more on the spectral range, spectral or spatial resolutions were important for the supervised classifiers. The Support Vector Machine (SVM) was found to perform better than other classification methods for the HSI2 images over all twenty-two study sites with the overall accuracy (OA) ranging from 82.6%–97.5% for VIS, and 81.5%–95.6 % for VIS + NIR. Considerably better performance of the supervised classifiers for the HSI2 VIS data over the Pleiades data (OA = 74.8–83.4%) suggested the importance of spectral resolution over spectral range (VIS vs. VIS+ NIR) for the supervised methods. The unsupervised classifiers exhibited low accuracy for both HSI2 VIS and UAV VIS imagery (OA< 30.0%) while the overall accuracy for the HSI2 VIS+ NIR and Pleiades data ranged from 60.4%–78.4 % and 42.1%–66.4%, respectively, suggesting the importance of spectral range for the unsupervised classifiers.     

Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

The underwater swimming manipulator (USM) is a snake‐like, multi‐articulated, underwater robot that is equipped with thrusters. One of the main purposes of the USM is to act like an underwater floating base manipulator. As such, it is essential to achieve good station‐keeping and trajectory tracking performance for the USM by using the thrusters and by using the joints to attain the desired position and orientation of the head and tail of the USM. In this ‘paper, we propose a sliding mode control (SMC) law, specifically the super‐twisting algorithm with adaptive gains, for the trajectory tracking of the USM's centre of mass. A higher‐order sliding mode observer is proposed for state estimation. Furthermore, we show the ultimate boundedness of the tracking errors. We demonstrate the applicability of the proposed control law and show that it leads to better performance than a linear PD‐controller.     

Theory‐Guided Synthesis of a Metastable Lead‐Free Piezoelectric Polymorph

Many technologically critical materials are metastable under ambient conditions, yet the understanding of how to rationally design and guide the synthesis of these materials is limited. This work presents an integrated approach that targets a metastable lead‐free piezoelectric polymorph of SrHfO₃. First‐principles calculations predict that the previous experimentally unrealized, metastable P4mm phase of SrHfO₃ should exhibit a direct piezoelectric response (d₃₃) of 36.9 pC N^?1 (compared to d₃₃ = 0 for the ground state). Combining computationally optimized substrate selection and synthesis conditions lead to the epitaxial stabilization of the polar P4mm phase of SrHfO₃ on SrTiO₃. The films are structurally consistent with the theory predictions. A ferroelectric‐induced large signal effective converse piezoelectric response of 5.2 pm V^?1 for a 35 nm film is observed, indicating the ability to predict and target multifunctionality. This illustrates a coupled theory‐experimental approach to the discovery and realization of new multifunctional polymorphs.     

The growing complexity in invention process

Technological and design process complexities may pose challenges to engineering design and related outcomes through invention. Understanding the trends related to the complexity of inventions and invention processes is crucial for informing engineering design research and education for invention, but has not been formally developed in the design literature. Herein, we utilize a set of patent-based metrics, drawn from complex systems research and engineering design research, to detect various aspects of the complexity in invention processes. By an analysis of U.S. patents from 1975 to 2011, our results suggest that technology inventions have been increasingly (1) requiring larger teams and more distant collaboration, (2) integrating a growing base of prior technologies, and (3) delivering more systemic and integrative new technologies. These trends may positively reinforce each other so as to contribute to a continual growth of the complexity in invention processes. Individual productivity for invention is also in decline, as we measured from the patent data. These findings suggest the increasing importance of research, education and application of complex system analysis methods and tools to control and manage the complexity in invention processes.     

Evaluation of Simple and Inexpensive High-Throughput Methods for Phytic Acid Determination

High‐throughput/low‐cost/low‐tech methods for phytic acid determination that are sufficiently accurate and reproducible would be of value in plant genetics, crop breeding and in the food and feed industries. Variants of two candidate methods, those described by Vaintraub and Lapteva (Anal Biochem 175:227–24, 1988 ; “VL” methods) and Huang and Lantzsch (J Sci Food Agric 34:1423–1426, 1983 ; “HL” methods), were evaluated. The primary concern with these methods is that, due to interference of matrix constituents including inorganic P, they can overestimate phytic acid and are ineffective at low levels of phytic acid. Twelve seed flours, representing lines of soybean, maize, barley and dry bean, containing a wide range of phytic acid levels, were analyzed by a minimum of eight cooperating laboratories using three variants of the VL method and two variants of the HL method. No method had consistently acceptable (?2.0”) “Horwitz ratios”, a measure of reproducibility, although some treatments approached that. For example, one variant of the VL method when used to assay a soybean flour with a “standard” level of phytic acid had a Horwitz ratio of 2.15. Some variants of the VL method were adequate for analyses of cereal grains regardless of phytic acid level but none accurately measured phytic acid when at low levels in soybean flours. One variant of the HL method in which the 0.2 N HCl extraction media is modified to contain 10% Na₂SO₄, did accurately measure phytic acid levels in both cereal and legume flours regardless of endogenous phytic acid levels or matrix constituents.     

Memory bias for threatening information in anxiety and anxiety disorders: A meta-analytic review.

Although some theories suggest that anxious individuals selectively remember threatening stimuli, findings remain contradictory despite a considerable amount of research. A quantitative integration of 165 studies with 9,046 participants (clinical and nonclinical samples) examined whether a memory bias exists and which moderator variables influence its magnitude. Implicit memory bias was investigated in lexical decision/stimulus identification and word-stem completion paradigms; explicit memory bias was investigated in recognition and recall paradigms. Overall, effect sizes showed no significant impact of anxiety on implicit memory and recognition. Analyses indicated a memory bias for recall, whose magnitude depended on experimental study procedures like the encoding procedure or retention interval. Anxiety influenced recollection of previous experiences; anxious individuals favored threat-related information. Across all paradigms, clinical status was not significantly linked to effect sizes, indicating no qualitative difference in information processing between anxiety patients and high-anxious persons. The large discrepancy between study effects in recall and recognition indicates that future research is needed to identify moderator variables for avoidant and preferred remembering. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Childhood physical abuse, attachment, and adult social support: Test of a mediational model.

This study examined the mediating role of attachment on the relationship between childhood physical abuse and perceived social support in adulthood. The 2 underlying dimensions of attachment, view of self and view of other, were both hypothesized to be potential mediators. Young adults, with and without a history of childhood physical abuse, completed a series of questionnaires inquiring about past abuse experiences and current levels of attachment and social support. Results indicated a robust mediational effect. Namely, both attachment variables were significant mediators in the relationship between childhood physical abuse and social support. In addition, the mediation occurred across all sources of social support, that is, social support from family/close friends, peers, and authority figures. Theoretical and clinical implications are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)