Master of Science

thesisDuring reconstructive and free tissue transfer surgeries it is often necessary to cut and reattach multiple vessels. The current method of vessel anastomosis is traditional hand suturing. The scope of this venture is to create a commercially available vascular coupling device (VCD) that would allow surgeons to quickly attach vessels together. The VCD is designed to increase reliability and reduce the amount of time spent on connecting two vessels. Hand suturing a vessel is time consuming (20-30 minutes) and difficult (requires a skilled surgeon). The method that has been developed can reduce the amount of time in the operating room by 75% and provides a superior anastomosis. In order to reach this level of improvement a set of installation tools was developed. These tools compliment the VCD and perform the necessary functions to consistently anastomise vessels. These tools were developed using laser machining techniques developed for this project. The laser manufacturing techniques allowed for the rapid development of the VCD and its supporting tools. With further development the VCD will become an important tool for the microsurgical community

RNA conformational changes in the life cycles of RNA viruses, viroids, and virus-associated RNAs

The rugged nature of the RNA structural free energy landscape allows cellular RNAs to respond to environmental conditions or fluctuating levels of effector molecules by undergoing dynamic conformational changes that switch on or off activities such as catalysis, transcription or translation. Infectious RNAs must also temporally control incompatible activities and rapidly complete their life cycle before being targeted by cellular defenses. Viral genomic RNAs must switch between translation and replication, and untranslated subviral RNAs must control other activities such as RNA editing or self-cleavage. Unlike well characterized riboswitches in cellular RNAs, the control of infectious RNA activities by altering the configuration of functional RNA domains has only recently been recognized. In this review, we will present some of these molecular rearrangements found in RNA viruses, viroids and virus-associated RNAs, relating how these dynamic regions were discovered, the activities that might be regulated, and what factors or conditions might cause a switch between conformations

Creating a web page for the Professional and Scientific Council at the University of Northern Iowa

A web site was created for the Professional and Scientific Council at the University of Northern Iowa. This site can be visited at www.uni.edu/ps_council. This site was created as a resource for the Professional and Scientific Staff. It includes links to payroll and benefits, along with background of the council, listing of the council members and information on meetings and monthly events. The methodology used to create the site will be addressed which will include discussion of why to build a site, categories of sites, planning the site, the design process, design principles and the presentation of information on the web page. The project will be briefly discussed along with what is contained in the Appendices. Conclusions and recommendations will be given on good and bad design features, costs of building a site and ideas will be given on how to market the site

A direct disodium dihydrogen ethylenediaminetetraacetate titration procedure for magnesium in limestone

Digitized 2007 AES.Includes bibliographical references (page 10)

Direct ethylenediaminetetraacetate titration procedure for calcium in biological substances : anion exchange separation of phosphate

Digitized 2007 AES.Includes bibliographical references (page 10)

IJA: An Efficient Algorithm for Query Processing in Sensor Networks

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm

Extinction Coefficient of Gold Nanostars

Gold nanostars (NStars) are highly attractive for biological applications due to their surface chemistry, facile synthesis, and optical properties. Here, we synthesize NStars in HEPES buffer at different HEPES/Au ratios, producing NStars of different sizes and shapes and therefore varying optical properties. We measure the extinction coefficient of the synthesized NStars at their maximum surface plasmon resonances (SPRs), which range from 5.7 × 10⁸ to 26.8 × 10⁸ M⁻¹ cm⁻¹. Measured values correlate with those obtained from theoretical models of the NStars using the discrete dipole approximation (DDA), which we use to simulate the extinction spectra of the nanostars. Finally, because NStars are typically used in biological applications, we conjugate DNA and antibodies to the NStars and calculate the footprint of the bound biomolecules.United States. National Institutes of Health (AI100190

Rapid Diagnostics for Infectious Disease using Noble Metal Nanoparticles

Rapid point-of-care (POC) diagnostic devices are needed for field-forward screening of severe acute systemic febrile illnesses such as dengue, Ebola, chikungunya, and others. Multiplexed rapid lateral flow diagnostics have the potential to distinguish among multiple pathogens, thereby facilitating diagnosis and improving patient care. We present a platform for multiplexed pathogen detection which uses gold or silver nanoparticles conjugated to antibodies to sense the presence of biomarkers for different infectious diseases. We exploit the size-dependent optical properties of Ag NPs to construct a multiplexed paperfluidic lateral flow POC sensor. AgNPs of different sizes were conjugated to antibodies that bind to specific biomarkers. Red AgNPs were conjugated to antibodies that could recognize the glycoprotein for Ebola virus, green AgNPs to those that could recognize nonstructural protein 1 for dengue virus, and orange AgNPs for non structural protein 1 for yellow fever virus. Presence of each of the biomarkers resulted in a different colored band on the test line in the lateral flow test. Thus, we were able to use NP color to distinguish among three pathogens that cause a febrile illness. Because positive test lines can be imaged by eye or a mobile phone camera, the approach is adaptable to low-resource, widely deployable settings. This design requires no external excitation source and permits multiplexed analysis in a single channel, facilitating integration and manufacturing. We will also discuss engineering the nanoparticle physical properties and surface chemistry for improving detection and also optimizing device properties, and expansion of the device to detect other diseases

Human induced pluripotent stem cell-derived glial cells and neural progenitors display divergent responses to Zika and dengue infections

Maternal Zika virus (ZIKV) infection during pregnancy is recognized as the cause of an epidemic of microcephaly and other neurological anomalies in human fetuses. It remains unclear how ZIKV accesses the highly vulnerable population of neural progenitors of the fetal central nervous system (CNS), and which cell types of the CNS may be viral reservoirs. In contrast, the related dengue virus (DENV) does not elicit teratogenicity. To model viral interaction with cells of the fetal CNS in vitro, we investigated the tropism of ZIKV and DENV for different induced pluripotent stem cell-derived human cells, with a particular focus on microglia-like cells. We show that ZIKV infected isogenic neural progenitors, astrocytes, and microglia-like cells (pMGLs), but was only cytotoxic to neural progenitors. Infected glial cells propagated ZIKV and maintained ZIKV load over time, leading to viral spread to susceptible cells. DENV triggered stronger immune responses and could be cleared by neural and glial cells more efficiently. pMGLs, when cocultured with neural spheroids, invaded the tissue and, when infected with ZIKV, initiated neural infection. Since microglia derive from primitive macrophages originating in proximity to the maternal vasculature, they may act as a viral reservoir for ZIKV and establish infection of the fetal brain. Infection of immature neural stem cells by invading microglia may occur in the early stages of pregnancy, before angiogenesis in the brain rudiments. Our data are also consistent with ZIKV and DENV affecting the integrity of the blood–brain barrier, thus allowing infection of the brain later in life. Keywords: Zika; microglia; organoids; interferon; iPSNational Institutes of Health (U.S.) (Grant AI100190

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google's PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4's performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions