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Articles 1 - 6 of 6
Full-Text Articles in Medicine and Health Sciences
Inference Of Language Functional Network In Healthy, Cancerous And Bilingual Brains By Fmri And Network Modeling, Qiongge Li
Dissertations, Theses, and Capstone Projects
We study the underlying mechanism by which language processing occurs in the human brain using inference methods on functional magnetic resonance imaging data. The data analyzed stems from several cohorts of subjects; a monolingual group, a bilingual group, a healthy control group and one diseased case. We applied a complex statistical inference pipeline to determine the network structure of brain components involved with language. This healthy network reveals a fully connected triangular relationship between the pre-Supplementary Motor Area (pre-SMA), the Broca's Area (BA), and the ventral Pre-Motor Area (PreMA) in the left hemisphere. This "triangle'' shows consistently in all the …
Development Of A Screening Method For Drugs Of Abuse By Direct Analysis Of Dried Urine Spots Coupled To Mass Spectrometry, Melanie Goldstein
Development Of A Screening Method For Drugs Of Abuse By Direct Analysis Of Dried Urine Spots Coupled To Mass Spectrometry, Melanie Goldstein
Student Theses
Fast and easy screening procedures are essential in any forensic toxicology laboratory to differentiate negative samples from presumptive positive cases. Immunoassay techniques, such as enzyme multiplied immunoassay technique (EMIT), are routinely employed as screening procedures. However, these techniques lack specificity (only differentiate group of drugs and not individual compounds) and it is difficult to add new compounds to the panel. Direct analysis of dried urine spots (DUS) by mass spectrometry (MS) offers a novel strategy to overcome these issues. DUS offer an improved storage alternative for biological samples, reducing costs and space requirements. In this work, an original method to …
Determination Of Anxiolytic And Antidepressant Medicines In New York City Wastewater Samples, Jasmine J. Gayle
Determination Of Anxiolytic And Antidepressant Medicines In New York City Wastewater Samples, Jasmine J. Gayle
Student Theses
Wastewater-based epidemiology (WBE) provides information about a population’s exposure to certain chemical agents, such as drugs of abuse and medicines, by the analysis of human biomarkers, also known as excretion products, in wastewater samples. Although this is a growing field worldwide, mainly in Europe, Oceania, and Asia, limited data from the US are currently available. We developed and validated an analytical method to quantitatively and qualitatively determine the presence of commonly prescribed drugs to treat anxiety (alprazolam, buspirone, clonazepam, lorazepam, and propranolol) and depression (bupropion, citalopram, clomipramine, duloxetine, fluoxetine, imipramine, paroxetine, sertraline, and venlafaxine) in wastewater using liquid chromatography tandem …
A Pretargeted Spect Imaging Strategy Employing Technetium-99m Based On Bioorthogonal Diels-Alder Click Chemistry, Justin H. Walsh
A Pretargeted Spect Imaging Strategy Employing Technetium-99m Based On Bioorthogonal Diels-Alder Click Chemistry, Justin H. Walsh
Dissertations, Theses, and Capstone Projects
A series of related N3S 99mTc-peptide complexes were synthesized and tested for use in pretargeting SPECT imaging that utilizes the bioorthogonal Diels-Alder click reaction between tetrazine (Tz) and transcyclooctene (TCO). The objective was to optimize the excretory pathways of the 99mTc-peptide complexes for maximum tumor targeting with the in vivo “click” and minimum non-target uptake. The 99mTc–tetrazine constructs were prepared by reaction of 99mTc-peptide complexes (99mTc-FKC, 99mTc-FKCR, 99mTc-DKC, and 99mTc-SKC) with Tz-NHS or Tz-PEG5-NHS to form 99mTc FK(Tz)C, 99mTc-FK(PEG5-Tz)CR, 99mTc-DK(PEG5-Tz)C, …
Deep Learning Based Medical Image Analysis With Limited Data, Jiaxing Tan
Deep Learning Based Medical Image Analysis With Limited Data, Jiaxing Tan
Dissertations, Theses, and Capstone Projects
Deep Learning Methods have shown its great effort in the area of Computer Vision. However, when solving the problems of medical imaging, deep learning’s power is confined by limited data available. We present a series of novel methodologies for solving medical imaging analysis problems with limited Computed tomography (CT) scans available. Our method, based on deep learning, with different strategies, including using Generative Adversar- ial Networks, two-stage training, infusing the expert knowledge, voting based or converting to other space, solves the data set limitation issue for the cur- rent medical imaging problems, specifically cancer detection and diagnosis, and shows very …
Using Fundamental Properties Of Light To Investigate Photonic Effects In Condensed Matter And Biological Tissues, Laura A. Sordillo
Using Fundamental Properties Of Light To Investigate Photonic Effects In Condensed Matter And Biological Tissues, Laura A. Sordillo
Dissertations and Theses
Light possesses characteristics such as polarization, wavelength and coherence. The interaction of light and matter, whether in a semiconductor or in a biological sample, can reveal important information about the internal properties of a system. My thesis focuses on two areas: photocarriers in gallium arsenide and biomedical optics. Varying the excitation wavelength can be used to study both biological tissue and condensed matter. I altered the excitation wavelengths to be in the longer near-infrared (NIR) optical windows, in the shortwave infrared (SWIR) range, a wavelength region previously thought to be unusable for medical imaging. With this method, I acquired high …