64 research outputs found

    Blood Politics, Ethnic Identity, and Racial Misclassification among American Indians and Alaska Natives

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    Misclassification of race in medical and mortality records has long been documented as an issue in American Indian/Alaska Native data. Yet, little has been shared in a cohesive narrative which outlines why misclassification of American Indian/Alaska Native identity occurs. The purpose of this paper is to provide a summary of the current state of the science in racial misclassification among American Indians and Alaska Natives. We also provide a historical context on the importance of this problem and describe the ongoing political processes that both affect racial misclassification and contribute to the context of American Indian and Alaska Native identity

    Synthesis of Janus compounds for the recognition of G-U mismatched nucleobase pairs

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    The design and synthesis of two Janus-type heterocycles with the capacity to simultaneously recognize guanine and uracyl in G-U mismatched pairs through complementary hydrogen bond pairing is described. Both compounds were conveniently functionalized with a carboxylic function and efficiently attached to a tripeptide sequence by using solid-phase methodologies. Ligands based on the derivatization of such Janus compounds with a small aminoglycoside, neamine, and its guanidinylated analogue have been synthesized, and their interaction with Tau RNA has been investigated by using several biophysical techniques, including UV-monitored melting curves, fluorescence titration experiments, and 1H NMR. The overall results indicated that Janus-neamine/guanidinoneamine showed some preference for the +3 mutated RNA sequence associated with the development of some tauopathies, although preliminary NMR studies have not confirmed binding to G-U pairs. Moreover, a good correlation has been found between the RNA binding affinity of such Janus-containing ligands and their ability to stabilize this secondary structure upon complexation

    A Self-Assembling Lanthanide Molecular Nanoparticle for Optical Imaging

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    Chromophores that incorporate f-block elements have considerable potential for use in bioimaging applications because of their advantageous photophysical properties compared to organic dye, which are currently widely used. We are developing new classes of lanthanide-based self-assembling molecular nanoparticles as reporters for imaging and as multi-functional nanoprobes or nanosensors for use with biological samples. One class of these materials, which we call lanthanide "nano-drums", are homogeneous 4d-4f clusters approximately 25 to 30 angstrom in diameter. These are capable of emitting from the visible to near-infrared wavelengths. Here, we present the synthesis, crystal structure, photophysical properties and comparative cytotoxicity data for a 32 metal Eu-Cd nano-drum [Eu8Cd24L12(OAc)(48)] (1). We also explored the imaging capabilities of this nano-drum using epifluorescence, TIRF, and two-photon microscopy platforms.Welch Foundation F-816, F-1018, F1515Ministry of High Education (MOHE), Malaysia under High Impact Research (HIR) - MOHE project UM.C/625/1/HIR/MoE/CHAN/13/6 H-50001-00-A000034NIH/NIAID 1U01AI078008-3Centre for Blast Injury Study at Imperial College LondonCPRIT R1003NIH-NCI CA68682National Institutes of HealthNational Science FoundationCancer Prevention Research Institute of TexasNational Science Foundation CHE-0741973Chemistr

    Machine learning for estimation of building energy consumption and performance:a review

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    Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

    Blood Politics, Ethnic Identity, and Racial Misclassification among American Indians and Alaska Natives

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    Misclassification of race in medical and mortality records has long been documented as an issue in American Indian/Alaska Native data. Yet, little has been shared in a cohesive narrative which outlines why misclassification of American Indian/Alaska Native identity occurs. The purpose of this paper is to provide a summary of the current state of the science in racial misclassification among American Indians and Alaska Natives. We also provide a historical context on the importance of this problem and describe the ongoing political processes that both affect racial misclassification and contribute to the context of American Indian and Alaska Native identity
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