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Arc Flash Incidents in Non-Residential Buildings: Data Analysis
Get PDFOccupational electrical incidents cause thousands of injuries each year in the United States. Among these incidents, arc flash events can result in serious injuries or fatalities, extensive damage to equipment, and economic losses.
Data on electrical incidents are reported by the Bureau of Labor Statistics (BLS), the Occupational Safety and Health Administration (OSHA), the National Institute for Occupational Safety and Health (NIOSH), and the Department of Energy (DOE). These data sources have different objectives and reporting thresholds. No single source provides a comprehensive and detailed database on arc flash incidents. The BLS database provides an overview of the aggregated number of occupational electrical injuries, while the OSHA and NIOSH databases provide investigation reports on selected incidents. It is estimated that, each year, OSHA and NIOSH cover approximately 3% to 10% of the injuries reported in the BLS database. The DOE database is not accessible to the public.
The OSHA and NIOSH databases include 1291 investigation reports relevant to arc flash events for the period from the early 1980s to 2022. These reports cover 1823 injuries and 277 fatalities. The reports can be searched by keywords and provide a description of the incidents mostly in free text, with limited categorized information. A detailed review of these 1291 reports was completed to construct a database with categorized information about the context, equipment, and cause of the arc flash incidents.
The data analysis revealed that arc flash incidents, injuries, and fatalities occurred both with low (V≤1000 V) and high (V>1000 V) voltage equipment, and at a broad range of ampacity. Incidents occur with a broad variety of pieces of equipment, the most frequent being powerlines, meters/testers/test equipment, wires and cables, panelboards, and circuit breakers. The use of tools such as screwdrivers is also frequently mentioned in the reports. However, the reports do not provide sufficient technical details to pinpoint the specific location within the equipment where the incident occurred.
It was also found that a number of incidents occurred during installation or maintenance work by qualified electrician workers. Operations of cleaning, repair, and trimming trees were also reported, in which the injured worker was frequently not a qualified worker. Meanwhile, an analysis of the error precursors showed that ‘human nature’ and ‘individual capability’ were the two most common error precursors, including lack of use of proper PPE and failure to de-energize the equipment. These data suggest that improving arc flash safety requires broad efforts in safety for both qualified and unqualified workers, and both planned and unplanned electrical work.
The compiled data can enhance understanding of the factors leading to arc flash incidents and injuries. Most importantly, it can help pinpoint areas for improvements in arc flash safety and enhancement of best practices, codes, and standards. Meanwhile, the data collection effort highlighted hurdles associated with the data availability and quality on arc flash incidents. Improvements in reporting of arc flash incidents in government databases, in terms of coverage, data granularity, and structuring of the data and metadata, would be beneficial to support incident analyses and recommendations for safety improvements
Development and Characterization of Biomaterials for T Cell-Based Immunotherapy
Get PDFCancer immunotherapy, specifically T cell based therapy, has renewed hope in next generation cancer treatments. As living drugs, T cells have the ability to traffic directly to the malignant tissue, kill cancer cells with high specificity, and remain in the body long term. Despite promising clinical results, major challenges still hinder the widespread use of T cell immunotherapies, including cost, difficult manufacturing, and variable response rates. To address these challenges, I developed and characterized biomaterials for the activation and expansion of therapeutic T cells. Through this work, I developed the first biomaterial scaffold for direct, in vivo, antigen-specific activation of CD8+ T cells, termed the artificial lymph node (aLN). The aLN, an injectable hydrogel with T cell stimulating signals, is able to expand rare tumor-specific T cells in situ, bypassing expensive and labor-intensive manufacturing steps that are usually involved in T cell therapies. In addition to providing a promising new therapeutic strategy, the aLN allows us to better understand the role of helper cells in T cell activation as well as the formation of immune niches in vivo. In addition to the aLN, I helped in the development of other biomaterial-based T cell stimulating platforms including biodegradable artificial antigen presenting cells for cancer therapy and magnetic nanoparticles for detection of SARS-CoV-2 reactive T cells. Together, these studies have contributed to our understanding of T cell immunobiology and have provided proof-of-concept for several new therapeutic platforms
ANALYZING THE IMPACT OF MUTATIONS IN LMNA AND ZMPSTE24 ON PRELAMIN A CLEAVAGE, PROGEROID DISEASES AND TREATMENT
No full textThe molecular pathways that promote physiological aging are not well understood. However, the study of rare premature aging disease such as
Hutchinson-Gilford Progeria Syndrome (HGPS) and Mandibuloacral Dysplasia
(MAD-B) can potentially reveal mechanisms that contribute to both accelerated aging diseases and physiological aging. HGPS and MAD-B result from defective biogenesis of the nuclear scaffold protein lamin A, specifically in the final cleavage step of the precursor, prelamin A, which is mediated by the zinc
metalloprotease ZMPSTE24. The aims of this dissertation are to elucidate the
mechanism of prelamin A recognition by ZMPSTE24, to examine the role of
specific LMNA and ZMPSTE24 mutations in disease, and to determine whether a
processing-related treatment can alleviate disease-causing effects.
Chapter I presents an overview of the biology of lamin A, its processing
pathway, and ZMPSTE24. It also summarizes commonalities of symptoms
between LMNA- and ZMPSTE24-linked laminopathies.
Chapter II presents an analysis of the substrate requirements for prelamin
A cleavage, which I performed collaboratively with other laboratory members. My work assessed the effect of alterations of the 15 carboxyl-terminal amino acids of prelamin A and showed that ZMPSTE24 has considerable flexibility in terms of its substrate recognition capabilities.
Chapter III presents studies conducted in collaboration with the Worman
laboratory, which generated a mouse model homozygous for the Lmna
substitution mutation L648R which results in an uncleavable prelamin A. This “prelamin A-only" mouse model recapitulates phenotypes stemming from
accumulation of full length prelamin A. My work showed that embryonic fibroblasts from this mouse have nuclear abnormalities that can be corrected by
treatment with a farnesyltransferase inhibitor (FTI).
Chapter IV examines the potential therapeutic benefits of treatment with
the FTI lonafarnib in patients with MAD-B by testing its effects on patient-derived
ZMPSTE24-deficient fibroblasts. My work showed that lonafarnib treatment
improves nuclear abnormalities observed in these patient cells, suggesting that
lonafarnib may be beneficial not only for HGPS, but also MAD-B patients. I also
showed that fibroblasts from patients with Atypical Progeroid Syndrome due to
LMNA mutations and fibroblasts carrying another LMNA variant, R644C, exhibit
no prelamin A processing defects and do not benefit from FTI treatment
DEVELOPING NOVEL TECHNIQUES TO MEASURE TRANSPORT PROPERTIES OF PLANETARY BUILDING BLOCKS
No full textIn this dissertation, I develop novel laser-compression techniques to measure the viscosity and thermal conductivity of geologically important materials at high pressures and temperatures. I developed two complementary techniques to measure the viscosity of materials, and I conducted experiments on MgO, which is the second most abundant mineral in the lower mantle. I present the first measurement of MgO viscosity at lower mantle pressures. I also developed and applied an analysis framework for previously collected but unpublished data, applying a new technique to measure the thermal conductivity of iron, which is the main constituent of the core. I give initial results based on my analysis pipeline and design improved experiments.
Chapter 2 details the development and results of the Richtmyer-Meshkov Growth method of measuring viscosity at high pressures. I present results from multiple campaigns conducted at the OMEGA-EP laser, which showcase the first-ever measurement of MgO viscosity at lower mantle pressures. This measurement brings us a step closer to constraining the viscosity of the lower mantle, which is crucial for modeling terrestrial planetary interiors.
Chapter 3 covers the analysis framework I created to analyze data from stagnating plasma piston experiments conducted with the intent of measuring the thermal conductivity of iron at high pressures and temperatures. The framework consists of modeling the experiments with a 1D finite element mesh and optimizing the thermal conductivity parameters using a differential evolution optimization algorithm. I present results including a wide range of assumptions. This quantity is important because it determines the driving mechanism of outer core convection, which creates the Earth's magnetic field.
Chapter 4 is about detailed plans for future experiments. In this chapter, I analyze the founding assumption behind the stagnating plasma piston thermal conductivity technique and isolate ways to answer some of the outstanding questions. I give designs for future experiments. I also detail my work on designing a second method for measuring the viscosity of materials at high pressures
MEASURING LIPOPROTEIN KINETICS IN ZEBRAFISH TO CHARACTERIZE NEW REGULATORS OF LIPOPROTEIN METABOLISM
No full textLipids are critical for life and require lipoproteins to navigate the aqueous environment of the blood. However, high levels of apolipoprotein B (APOB) containing lipoproteins (B-lps) have been linked to increased cardiovascular disease (CVD) risk. While standard methods for assessing CVD risk focus on lipoprotein levels, understanding the reasons behind elevated B-lp levels can require a closer look at B-lp kinetics. Presently, B-lp turnover studies require the use of radio-labeled isotopes and computational modeling.
Genetic studies continue to identify new genes affecting B-lps, often without mechanistic insight, including the asialoglycoprotein receptor 1 (ASGR1) gene. Human mutations in ASGR1 lower LDL and disproportionally reduce the risk for CVD. To understand how ASGR1 affects B-lps, I identified the zebrafish ortholog asgr1a. Surprisingly, asgr1a mutant adults for two CRISPR-induced alleles exhibited reduced steatosis when fed a Western diet and secreted the excess cholesterol in their feces while not showing any changes in B-lp numbers or sizes.
This led me to suspect that asgr1a might affect B-lp kinetics. Additionally, the lab had identified and characterized mutations in mttpc655 and pla2g12bsa659 that impaired the triglyceride loading of B-lps, resulting in smaller B-lps. Intriguingly, these mutants did not present with impacts on the vasculature or steatosis.
To study lipoprotein turnover in zebrafish, I developed LipoTimer, a fusion protein reporter of the photoconvertible fluorophore Dendra2 to the endogenous locus of apoBb.1, the APOB ortholog of zebrafish. UV light exposure shifts the emission spectrum of Dendra2 from green to red, allowing us to follow red-state ApoB-Dendra2 labeled B-lps. Using the LipoTimer, we discovered that mttpc655 and pla2g12bsa659 mutant larvae have significantly shorter B-lp half-life of whole-body and circulating B-lps. Adapting the LipoTimer assay for juvenile zebrafish, I found that a high-cholesterol diet slows down the B-lps turnover, likely through saturation of lipoprotein lipase.
By adapting LipoTimer for tissue-specific B-lp turnover and adult animal studies, we may uncover the effects of asgr1a on lipoprotein kinetics. LipoTimer’s potential to directly measure B-lp half-life in diverse conditions, mutants, and drug studies makes it a valuable tool for understanding lipoprotein turnover
Beta-testing a peer-to-peer virtual helpdesk as part of a forward-thinking, responsive support and development plan.
Get PDFThis capstone project proposes a way to utilize the collective knowledge of university and institutional research administrators to provide knowledge, guidance, and assistance to each other via a peer-to-peer virtual helpdesk. These administrators support a trio of relevant constituencies: the individuals who conduct the research, the institutions that provide a home for the research, and the sponsors that support the research financially. Providing this service proves challenging due to the constantly mutating rules and nuances creating and governing research bureaucracy. These constantly shifting rules and exceptions are why “it depends” is a cliché widely thought of as the unofficial motto of research administrators (NCURA 2021).
Whether a research institution uses a centralized or decentralized approach to its administrative architecture, both methods rely on expert authoritative guidance from specialized departments. Unfortunately, these central offices often do not have enough staff to answer questions in a timeframe that works for a modern research administrator’s relentless schedule. Over the past three decades increased governmental regulations and capped administrative funding have resulted in more responsibility being transferred from the central offices to the unit-level administrators. Consequently, the administrators working at the departmental level cannot be responsive to their internal customers while waiting days, weeks, and sometimes longer for guidance, nor do they have the time to chase the answers externally. A peer-to-peer virtual helpdesk, may provide an online platform where administrators can post questions, reply to others, discuss concepts, and build a network. By doing so, they could create a powerful source of guidance and mentorship, fueled by the hard-won wisdom of their peers, that can help alleviate the pressure on departmental and central administrations
Microfluidics Meets Personalized Medicine: Unlocking Secrets in Cancer Cell Invasion and Metastasis
No full textThis research addresses the critical need to predict the spread of localized cancer, particularly in breast cancer and glioblastoma multiforme (GBM), where metastasis and invasion drastically reduces survival rates. We developed a microfluidic assay (MAqCI) to quantify highly migratory cells and their proliferation state, predicting metastatic and invasive potential accurately. Using this assay, we identified 17 upregulated genes common in breast cancer and GBM patients, which contribute to tumorigenesis. We evaluated the efficacy of antimetastatic drugs targeting these genes and extended the prognostic utility of MAqCI to clinical tumor models, including patient-derived xenografts and fresh tumor samples. Collaborating with institutions like the University of Maryland, Johns Hopkins School of Medicine, and Mayo Clinic Jacksonville, we conducted prospective prognostic studies to correctly predict patient survival times and evaluate patient responses to chemotherapy and FDA-approved drugs. Our work aims to develop personalized therapies and improve outcomes for patients with metastatic and highly invasive cancer
THE INTERPLAY OF MITOCHONDRIAL DNA, MATERNAL METABOLIC CONDITIONS, AND PSYCHOSOCIAL STRESS IN AUTISM SPECTRUM DISORDER (ASD)
Get PDFAutism spectrum disorder (ASD) is a neurodevelopmental disorder with heterogeneous manifestations and complicated etiology. Limited research has assessed the involvement of mitochondrial DNA (mtDNA) in autism etiology, particularly its integration with environmental factors. This dissertation sought to systematically examine the relationship between mtDNA measures in early life stage and childhood ASD-related outcomes, with a focus on the influence of mtDNA measures on autistic traits and their integration with prenatal environmental factors, leveraging data from the Boston Birth Cohort (BBC), a prospective birth cohort of predominantly urban, low-income, racial and ethnic minority population.
First, I investigated the association of cord blood mtDNA measures (mtDNA content and heteroplasmic mutations) with childhood autistic quantitative traits, which are assessed by the Social Communication Questionnaire (SCQ) and Social Responsiveness Scales (SRS). I found that having heteroplasmic mutations within functional genes was linked with a higher level of autistic traits; however, there was no significant association between mtDNA content and autistic traits.
Second, I assessed the joint association of maternal metabolic conditions (diabetes mellitus and pre-pregnancy obesity) and cord blood mtDNA measures with ASD clinical diagnosis and autistic traits. The results indicated a synergistic pattern, wherein the likelihood of ASD diagnosis increased substantially when maternal obesity concided with having any heteroplasmic mutation or when maternal diabetes coincided with a high mtDNA content level. There were statistical multiplicative interactions at near significance for the above joint associations.
Third, I evaluated the joint association of maternal perceived stress and cord blood mtDNA measures with ASD diagnosis and autistic traits. I found a statistically significant super-additive interaction between maternal stress and the presence of any heteroplasmic mutation in cord blood on the likelihood of ASD diagnosis. Similar patterns were observed when using the SCQ score as an outcome but lacked statistical interaction.
This dissertation advances the understanding of how cord blood mtDNA measures contribute to the development of ASD and sheds new insight on mitochondrial gene-environmental interaction in ASD. The findings can help improve early risk assessment and imply potential targets for public health and clinical practices
INVESTIGATING THE STRUCTURAL REQUISITES OF PHOTOPHYSICAL PROPERTIES IN FLUORESCENT BIOMOLECULES
No full textFluorescent probes are ubiquitous tools in biomedical research as they enable the visualization of dynamic processes in living organisms. It is imperative that we understand the photophysics of fluorescent biomolecules for an accurate understanding of their experimental readouts. In this dissertation, I seek to expand on our views about fluorescence that are relevant to biology, from fundamental excitation transfer dynamics to their efficacy and tunability in experimental contexts. In Chapter 2, I explore a machine learning approach to novel sequence design for fluorescent proteins (FPs). The complexity of FP chemistry makes the design of variants with optimized spectroscopic properties challenging. I hypothesized that a variational autoencoder approach would be able to predict spectroscopic properties from FP sequences, providing information that could guide future mutagenesis studies. I found that while our machine learning model performs well on our training data, it may not generalize to FP sequences outside of the training set. In Chapter 3, I examine the fundamental excitation transfer dynamics of FPs. FPs in close proximity exhibit photophysical effects that are consistent with excitonic coupling, including rapid energy transfer between fluorophores. I hypothesized that the FP β-barrel structure enables this quantum effect by protecting the chromophore from environmental decoherence. In this scenario, energy transfer faster than FRET should be observed in FP variants other than VenusA206. To validate this hypothesis, I built a TRFA instrument with improved time resolution and used it to measure energy transfer rates in a catalog of FP dimer variants. I found that four of these FP constructs exhibit energy transfer rates consistent with excitonic coupling. Finally, in Chapter 4, I assess the accuracy of single molecule FRET experiments in estimating subnanosecond molecular processes—specifically, the transition path, or the portion of a protein’s folding trajectory where it transitions from one stable state to another. I used molecular simulations to ask whether FRET is an accurate estimator of transition path times. I found that FRET data yields transition path times within a factor of 2–4 of the true values, but tends to systematically underestimate these times due to assumptions about transition path shape
