Biological applications of magnetic nanoparticles

In this review an overview about biological applications of magnetic colloidal nanoparticles will be given, which comprises their synthesis, characterization, and in vitro and in vivo applications. The potential future role of magnetic nanoparticles compared to other functional nanoparticles will be discussed by highlighting the possibility of integration with other nanostructures and with existing biotechnology as well as by pointing out the specific properties of magnetic colloids. Current limitations in the fabrication process and issues related with the outcome of the particles in the body will be also pointed out in order to address the remaining challenges for an extended application of magnetic nanoparticles in medicine.

Genitourinary applications of diffusion-weighted MR imaging in the pelvis

Diffusion-weighted (DW) magnetic resonance (MR) imaging has a large number of potential clinical applications in the female and male pelvis and can easily be added to any routine MR protocol. In the female pelvis, DW imaging allows improvement of staging in endometrial and cervical cancer, especially in locally advanced disease and in patients in whom contrast medium administration should be avoided. It can also be helpful in characterizing complex adnexal masses and in depicting recurrent tumor after treatment of various gynecologic malignancies. DW imaging shows promising results in monitoring treatment response in patients undergoing radiation therapy of cervical cancer. An increase in apparent diffusion coefficient (ADC) values of responders precedes changes in size and may therefore allow early assessment of treatment success. In the male pelvis, the detection of prostate cancer in the peripheral zone is relatively easier than in the central gland based on the underlying ADC values, whereas overlapping values reported in the central gland still need further research. DW imaging might also be applied in the noninvasive evaluation of bladder cancer to differentiate between superficial and muscle-invasive tumors. Initial promising results have been reported in differentiating benign from malignant pelvic lymph nodes based on the ADC values; however, larger-scale studies will be needed to allow the detection of lymph node metastases in an individual patient. Prerequisites for successfully performing DW imaging of the female and male pelvis are standardization of the DW imaging technique, including the choice of b values, administration of an antiperistaltic drug, and comparison of DW findings with those of morphologic MR imaging.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Extracranial applications of diffusion-weighted magnetic resonance imaging

Diffusion-weighted MRI has become more and more popular in the last couple of years. It is already an accepted diagnostic tool for patients with acute stroke, but is more difficult to use for extracranial applications due to technical challenges mostly related to motion sensitivity and susceptibility variations (e.g., respiration and air-tissue boundaries). However, thanks to the newer technical developments, applications of body DW-MRI are starting to emerge. In this review, we aim to provide an overview of the current status of the published data on DW-MRI in extracranial applications. A short introduction to the physical background of this promising technique is provided, followed by the current status, subdivided into three main topics, the functional evaluation, tissue characterization and therapy monitoring.

Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.

Sulfoxides as an intramolecular sulfenylating agent for indoles and diverse applications of the sulfide-sulfoxide redox cycle in organic chemistry

This dissertation involves study of various aspects of sulfoxide chemistry. Specifically designed t-butyl and propanenitrile sulfoxides tethered to indole-2-carboxamide were used as a source of intramolecular sulfenylating agents to synthesize novel indolo[3,2-b]-1-5-benzothiazepinones which are structurally analogous to the other biologically active benzothiazepinones. This study reveals that the intramolecular cyclization of sulfoxide follows an electrophilic sulfenylation (Sulfoxide Electrophilic Sulfenylation, SES) reaction pathway. Evidence of the absence of sulfenic acid as a transient reactive intermediate in such intramolecular cyclization is also provided. In another study, sulfoxide was used as a “protecting group” of thioether to synthesize 8-membered, indole substituted, thiazocine-2-acetic acid derivative via Ring Closing Metathesis (RCM). Protection (oxidation) of inert (to RCM) sulfide to sulfoxide followed by RCM produced cyclized product in good yields. Deprotection (reduction) of sulfoxide was achieved using Lawessons Reagent (L.R.). Application of the sulfide-sulfoxide redox cycle to solve the existing difficulties in using RCM methodology to thioethers is illustrated. A new design of a “molecular brake”, based on the sulfide-sulfoxide redox cycle is described. N-Ar rotation in simple isoindolines is controlled by the oxidation state of the proximate sulfur atom. Sulfide [S(II)] shows “free” [brake OFF] N-Ar rotation whereas sulfoxide displayed hindered [brake ON] N-Ar rotation. The semi-empirical molecular orbital (PM3) calculations revealed concerted pyramidalization of amidic nitrogen with N-Ar rotation.

Applications of finite geometries to designs and codes

This dissertation concerns the intersection of three areas of discrete mathematics: finite geometries, design theory, and coding theory. The central theme is the power of finite geometry designs, which are constructed from the points and t-dimensional subspaces of a projective or affine geometry. We use these designs to construct and analyze combinatorial objects which inherit their best properties from these geometric structures. A central question in the study of finite geometry designs is Hamada’s conjecture, which proposes that finite geometry designs are the unique designs with minimum p-rank among all designs with the same parameters. In this dissertation, we will examine several questions related to Hamada’s conjecture, including the existence of counterexamples. We will also study the applicability of certain decoding methods to known counterexamples. We begin by constructing an infinite family of counterexamples to Hamada’s conjecture. These designs are the first infinite class of counterexamples for the affine case of Hamada’s conjecture. We further demonstrate how these designs, along with the projective polarity designs of Jungnickel and Tonchev, admit majority-logic decoding schemes. The codes obtained from these polarity designs attain error-correcting performance which is, in certain cases, equal to that of the finite geometry designs from which they are derived. This further demonstrates the highly geometric structure maintained by these designs. Finite geometries also help us construct several types of quantum error-correcting codes. We use relatives of finite geometry designs to construct infinite families of q-ary quantum stabilizer codes. We also construct entanglement-assisted quantum error-correcting codes (EAQECCs) which admit a particularly efficient and effective error-correcting scheme, while also providing the first general method for constructing these quantum codes with known parameters and desirable properties. Finite geometry designs are used to give exceptional examples of these codes.

Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA

We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.

DEVELOPMENT AND APPLICATIONS OF GENOMIC RESOURCES FOR TWO NORTH AMERICAN HARDWOOD TAXA

Hardwoods comprise about half of the biomass of forestlands in North America and present many uses including economic, ecological and aesthetic functions. Forest trees rely on the genetic variation within tree populations to overcome the many biotic, abiotic, anthropogenic factors which are further worsened by climate change, that threaten their continued survival and functionality. To harness these inherent genetic variations of tree populations, informed knowledge of the genomic resources and techniques, which are currently lacking or very limited, are imperative for forest managers. The current study therefore aimed to develop genomic microsatellite markers for the leguminous tree species, honey locust, Gleditsia triacanthos L. and test their applicability in assessing genetic variation, estimation of gene flow patterns and identification of a full-sib mapping population. We also aimed to test the usefulness of already developed nuclear and gene-based microsatellite markers in delineation of species and taxonomic relationships between four of the taxonomically difficult Section Lobatae species (Quercus coccinea, Q. ellipsoidalis, Q. rubra and Q. velutina. We recorded 100% amplification of G. triacanthos genomic microsatellites developed using Illumina sequencing techniques in a panel of seven unrelated individuals with 14 of these showing high polymorphism and reproducibility. When characterized in 36 natural population samples, we recorded 20 alleles per locus with no indication for null alleles at 13 of the 14 microsatellites. This is the first report of genomic microsatellites for this species. Honey locust trees occur in fragmented populations of abandoned farmlands and pastures and is described as essentially dioecious. Pollen dispersal if the main source of gene flow within and between populations with the ability to offset the effects of random genetic drift. Factors known to influence gene include fragmentation and degree of isolation, which make the patterns gene flow in fragmented populations of honey locust a necessity for their sustainable management. In this follow-up study, we used a subset of nine of the 14 developed gSSRs to estimate gene flow and identify a full-sib mapping population in two isolated fragments of honey locust. Our analyses indicated that the majority of the seedlings (65-100% - at both strict and relaxed assignment thresholds) were sired by pollen from outside the two fragment populations. Only one selfing event was recorded confirming the functional dioeciousness of honey locust and that the seed parents are almost completely outcrossed. From the Butternut Valley, TN population, pollen donor genotypes were reconstructed and used in paternity assignment analyses to identify a relatively large full-sib family comprised of 149 individuals, proving the usefulness of isolated forest fragments in identification of full-sib families. In the Ames Plantation stand, contemporary pollen dispersal followed a fat-tailed exponential-power distribution, an indication of effective gene flow. Our estimate of δ was 4,282.28 m, suggesting that insect pollinators of honey locust disperse pollen over very long distances. The high proportion of pollen influx into our sampled population implies that our fragment population forms part of a large effectively reproducing population. The high tendency of oak species to hybridize while still maintaining their species identity make it difficult to resolve their taxonomic relationships. Oaks of the section Lobatae are famous in this regard and remain unresolved at both morphological and genetic markers. We applied 28 microsatellite markers including outlier loci with potential roles in reproductive isolation and adaptive divergence between species to natural populations of four known interfertile red oaks, Q. coccinea, Q. ellpsoidalis, Q. rubra and Q. velutina. To better resolve the taxonomic relationships in this difficult clade, we assigned individual samples to species, identified hybrids and introgressive forms and reconstructed phylogenetic relationships among the four species after exclusion of genetically intermediate individuals. Genetic assignment analyses identified four distinct species clusters, with Q. rubra most differentiated from the three other species, but also with a comparatively large number of misclassified individuals (7.14%), hybrids (7.14%) and introgressive forms (18.83%) between Q. ellipsoidalis and Q. velutina. After the exclusion of genetically intermediate individuals, Q. ellipsoidalis grouped as sister species to the largely parapatric Q. coccinea with high bootstrap support (91 %). Genetically intermediate forms in a mixed species stand were located proximate to both potential parental species, which supports recent hybridization of Q. velutina with both Q. ellipsoidalis and Q. rubra. Analyses of genome-wide patterns of interspecific differentiation can provide a better understanding of speciation processes and taxonomic relationships in this taxonomically difficult group of red oak species.

Musculoskeletal applications of flat-panel volume CT

Flat-panel volume computed tomography (fpVCT) is a recent development in imaging. We discuss some of the musculoskeletal applications of a high-resolution flat-panel CT scanner. FpVCT has four main advantages over conventional multidetector computed tomography (MDCT): high-resolution imaging; volumetric coverage; dynamic imaging; omni-scanning. The overall effective dose of fpVCT is comparable to that of MDCT scanning. Although current fpVCT technology has higher spatial resolution, its contrast resolution is slightly lower than that of MDCT (5-10HU vs. 1-3HU respectively). We discuss the efficacy and potential utility of fpVCT in various applications related to musculoskeletal radiology and review some novel applications for pediatric bones, soft tissues, tumor perfusion, and imaging of tissue-engineered bone growth. We further discuss high-resolution CT and omni-scanning (combines fluoroscopic and tomographic imaging).

Applications of Stable Isotope Ratio Analysis for Social Science Research

Stable Isotope Ratio Analysis (SIRA) is the measurement of variation in different isotopes of same elements in a material. This technique is well-established in the natural sciences and has been long part of the methodological arsenal in fields such as geology and biology. More recently this technique has begun to be utilized in the social sciences, moving from initial applications in anthropology to potential uses in geography, public health, forensic science, and others. This presentation will discuss the techniques behind SIRA, examples of current applications in the natural and social sciences, and potential avenues of future research.