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The Relationship between Eldercare Responsibilities and Work Outcomes: A Multi-method Approach
No full textAs the aging population continues to grow in the United States and worldwide, an increasing number of employees find themselves balancing work and eldercare responsibilities at home. Research in eldercare and work-family has predominantly focused on the adverse effects of eldercare, often resulting in the discrimination of employees with family caregiving responsibilities. In this thesis, I challenge the conventional conceptualization of eldercare as a burden and propose that eldercare involvement may yield positive effects. Furthermore, I comprehensively examine the impact of employee eldercare responsibilities on work outcomes while drawing comparisons with childcare responsibilities, using three groups – employees with eldercare responsibilities, employees with childcare responsibilities, and employees with both eldercare and childcare responsibilities in Study 3. Employing both qualitative and quantitative research methodologies, this thesis enriches the work-family literature by incorporating various mechanisms within the caregiving context. The investigation offers valuable implications for enhancing employee work outcomes and fostering an inclusive workplace environment
Direct and Indirect Factors Render LPS Essential to Gram-negative Bacterial Physiology
Get PDFFor single-celled organisms, the cell envelope is the thin barrier between life and death, between the self and the environment. Their survival depends on the integrity and maintenance of this envelope. The cell envelope of Gram-negative organisms is tripartite, consisting of a phospholipid inner membrane, an aqueous periplasmic space containing the peptidoglycan sacculus, and an asymmetric outer membrane bearing phospholipids on the inner leaflet and lipopolysaccharides (LPS) on the outer leaflet. Surface-exposed, highly immunoreactive, and essential to nearly all Gram-negative bacteria, LPS has been extensively studied for its roles in pathogenesis and immunobiology and as a potential therapeutic target for novel antibiotics. Despite advances in these areas, another aspect of LPS biology – its contribution to overall Gram-negative bacterial physiology – remains unclear. Although LPS has been implicated in various aspects of physiology, the primary essential contribution(s) of LPS to Gram-negative physiology are not known. This dissertation identifies factors – both direct and indirect – which render LPS essential to Gram-negative physiology. LPS has been implicated in both cell envelope rigidity and the coordination of cell division and separation. In Chapter 2, I use a combination of chemical and genetic approaches to test which of these roles – if either – is responsible for LPS essentiality in Escherichia coli and Klebsiella pnuemoniae. Further, I test the hypothesis that asynchronous biogenesis of the inner and outer membranes during LPS depletion is an additional factor contributing to LPS essentiality. I demonstrate that, although LPS is critical for cell envelope integrity, preserving cell envelope integrity is not sufficient to preserve culturability of LPS-depleted cells. Using a candidate gene screen to identify mutants with enhanced survival during LPS depletion, I demonstrate that deletion of factors which remove peptidoglycan crosslinks, which is predicted to increase cell wall rigidity, reduces susceptibility to the LPS synthesis inhibitor CHIR-090. However, these mutations are not sufficient to allow survival in the absence of LPS. Altogether, these data are consistent with a model in which cell envelope rigidity is one – but not the sole – factor responsible for LPS essentiality. In the same candidate gene screen, I found that mutations expected to enhance phospholipid retention in the outer leaflet of the outer membrane reduce susceptibility to CHIR-090. This finding is consistent with work in Acinetobacter baumannii demonstrating that biogenesis of the outer membrane in the absence of LPS is rate-limiting for growth. Further, mutations expected to reduce global lipid synthesis, thus reducing inner membrane synthesis to better match reduced outer membrane synthesis during LPS depletion, similarly reduce susceptibility. This data is consistent with known mechanisms of CHIR-090 resistance, which are thought to exhibit the same effect on membrane biogenesis rates. Although LPS has been implicated in cell division since the 1970s, the nature of that connection remains unclear. In this dissertation, I demonstrate that general enhancement of cell division is not sufficient to enhance survival of cells during LPS depletion. Instead, only the gain-of-function allele ftsA* reduced susceptibility to CHIR-090. Although the precise nature of this connection remains unclear, these results implicate the cell division protein FtsA in LPS essentiality by an unknown mechanism. Additionally, I identified two spontaneous mutants – a 6-bp deletion in marR, a regulator of multiple antibiotic resistance, and a transposition of an IS element into the promoter of the gene encoding Lon protease – that substantially reduce susceptibility to CHIR-090 despite exhibiting a decrease in LPS content of approximately 60% relative to untreated cells. Both mutations seem to result in accumulation of the positive regulator of multiple antibiotic resistance MarA. Overexpression of marA is sufficient to enhance survival during LPS depletion by both lpxC tCRISPRi and CHIR-090 treatment. These data argue against a strictly efflux model of resistance and suggest an as-yet undescribed mechanism of increased tolerance to LPS depletion. As a whole, this dissertation provides insight into the essential contributions of LPS to Gram-negative physiology, specifically through cell envelope rigidity, membrane homeostasis, and cell division. Further work in this area will provide a clearer understanding of Gram-negative physiology and, ultimately, a more thorough understanding of how to treat Gram-negative infections
Efficient packaging of HIV-1 genomes via recognition of its adenosine-rich content by a heterologous RNA-binding domain
Get PDFRNA-protein interactions underlie many key processes in viral replication and antiviral immune responses. In this thesis, I reported our investigations on the roles of two RNA-binding proteins, Gag and IFIT1, in mediating HIV-1 genome packaging and regulating innate immune gene expression, respectively. The HIV-1 genome comprises a dimer of unspliced, positive sense mRNA (gRNA) that is packaged with high efficiency, with more than 90% of viral particles containing two copies of gRNA. Gag is the major HIV-1 structural protein that coordinates all steps of virion assembly and possesses a nucleocapsid domain (NC) required for gRNA binding and genome packaging. In infected cells, viral RNA is surrounded by a vast excess of cellular RNAs. Thus, it was previously thought that HIV-1 achieves efficient genome packaging through the selective binding of gRNA by Gag, mediated by specific high-affinity interaction between NC and the cis-acting packaging signal Ψ located within the HIV-1 5’-UTR. However, deletion of regions in Ψ only modestly reduces genome packaging, which led us to hypothesize that there are additional accessory factors important for this process. RNA plays a structural role in HIV-1 virion assembly and Gag-Gag multimerization was recently found to be important for genome packaging. Thus, an emerging model posits that HIV-1 gRNA is packaged selectively because it is more efficient at driving Gag multimerization than cellular RNAs. However, the feature(s) of viral RNA that make it a suitable catalyst for Gag multimerization are not well understood. Gag was previously reported to change its RNA binding specificity throughout HIV-1 virion morphogenesis, switching from G/U-rich binding in the cytoplasm to purine-rich (A/G) binding at the PM and in immature virions. This switch was proposed to play a role in genome packaging because HIV-1 gRNA has an unusually biased nucleotide composition (~40% adenosine). I investigated whether the binding preference of Gag toward purine-rich motifs plays a role in HIV-1 genome packaging and, consequently, whether the adenosine (A) richness of HIV-1 gRNA plays an accessory role in genome packaging. To this end, we replaced NC with heterologous RNA binding domains (RBDs) derived from cellular RNA binding proteins of the hnRNP and SRSF families to generate Gag chimeras with altered RNA binding specificity. We identified one chimera, Gag-SRSF5, that packaged gRNA nearly as efficiently as WT. Unexpectedly, while Gag-SRSF5 is the sole exception, all Gag chimeras were able to find and retain gRNA at the PM at near WT level. However, past this stage of gRNA recruitment to the PM, the majority of Gag chimeras exhibited assembly defects and failed to form buds. Gag-SRSF5 variants with reduced RNA binding affinity towards purine-rich motifs and altered specificity for C/G- or G-rich motifs displayed reduction in genome packaging efficiency. Altogether these results suggest that the biased nucleotide composition of the HIV-1 genome serves as a molecular signature that facilitate efficient genome packaging by promoting rapid Gag multimerization on viral RNA. These results also provide further supporting evidence for the model where HIV-1 gRNA is packaged efficiently based on the kinetics of Gag multimerization, and not based on specific interaction between NC and Ψ because diverse RBDs could find and retain Ψ-containing gRNA at the PM. Another long-standing question in the field is how HIV-1 ensures the packaging of a gRNA dimer. We hypothesized that dimeric gRNA packaging requires a tight balancing of Gag binding affinity and avidity towards gRNA, where the late arriving pool of Gag molecules need to dissociate from the bound cellular or viral RNA before arriving at virion assembly sites to drive the growth of immature Gag lattices. Therefore we replaced NC with up to seven tandem Zn2+ fingers from cellular nucleic acid binding protein (Gag-CNBPs) and duplicated/triplicated NC to generate chimeras with enhanced RNA binding affinity/avidity. Despite binding to more than WT Gag in cells with increasing number of Zn2+ fingers as intended, none of the Gag-NCx2/3 and Gag-CNBP chimeras packaged gRNA more efficiently than WT. Nevertheless, increasing the number of Zn2+ fingers progressively enhanced gRNA localization at the PM and genome packaging efficiency. These data suggest that the RNA binding affinity of Gag needs to be above a certain threshold to ensure efficient packaging and there is a clear selection process at the plasma membrane that limits the amount of gRNA packaged into virions. All Gag chimeras are non-infectious. Thus, we next asked whether they could block infectious when co-assembled with WT Gag in virions. Co-transfection of Gag chimeras with WT Gag in virus-producing cells exerted dominant negative effects, severely blocking infection while having negligible effects on particle release and genome packaging. Given their potent antiviral effects, Gag chimeras, which can co-assemble with WT Gag in virions, could be developed into anti-HIV-1 therapeutics that pose high genetic barriers to virus evolving resistance. Lastly, I described our investigation on the cellular protein interferon-induced protein with tetratricopeptide repeats-1 (IFIT1). IFIT1 is an interferon stimulated gene (ISG) that blocks viral translation by binding to viral RNA lacking 2′-O methylation and interacting with cellular proteins involved in translation. Emerging evidence suggests that IFIT1 also plays a role in regulating immune gene expression at the transcriptional level during lipopolysaccharide (LPS) stimulation and at the translational level during IFN response. Thus I monitored global transcriptional and translational changes in WT versus IFIT1-knockout THP-1 cells treated with and without type I interferon (IFN) stimulation using RNA-seq and ribosome profiling, respectively. For both IFN-treated THP-1 cells, IFIT1 deletion led to the transcriptional upregulation of immune genes, including ISGs and cytokines. At the translational level, the expression of immune genes was also upregulated in the absence of IFIT1. Interestingly, a number of pro-inflammatory cytokine genes are translated less efficiently in THP-1 cells upon IFN stimulation in an IFIT1 independent manner. Together, these data suggest that IFIT1 negatively regulates the expression of certain immune genes during IFN stimulation and certain cytokine genes are subjected to translational control during IFN response
Investigating the determinants of influenza entry and spread in human airway cells using fluorescence microscopy
No full textInfluenza A virus (IAV) remains a significant global health challenge. IAV utilizes the receptor binding protein hemagglutinin (HA) and the receptor destroying protein neuraminidase (NA) to facilitate infection. The activities of these proteins affect multiple steps in IAV life cycle. However, it remains unclear how these IAV factors influence infection dynamics in the context of a complex cellular environment encountered in the respiratory tract. In this work, we use fluorescence microscopy and human airway epithelial cells to study influenza biology at the single-cell and single-virion level, revealing key insights into viral binding, entry, and spread. First, we focused on the cellular determinants of HA proteolytic activation. This process is essential for enabling HA to mediate viral entry. Using immunofluorescence, we observed cell-to-cell variability in HA activation efficiency. This offers a mechanistic explanation for the efficient yet incomplete activation observed at the population level. These results suggest that not all virions produced within a host cell population are equally infectious, highlighting the role of cellular factors in shaping viral fitness and infectivity. Second, we studied the role of NA activity during virus spread and discovered its ability to optimize the efficiency of viral transmission by cleaving the viral receptor at the infection sites. This allows the virus to seed productive infections locally while maximizing its potential to spread distantly. Lastly, we investigated how ciliated cells contribute to virus binding in human airway epithelia. By characterizing infections in samples from donors with primary ciliary dyskinesia (PCD), we found that ciliary beating is essential for IAV to reach the cell body of the ciliated cells for infection, while enhancing binding to other cell types. Beyond the investigation at single-cell and single-virion level, we pursued studies on molecular orientation and flexibility at single molecule level to elucidate how protein dynamics affect the interactions between influenza protein and antibody. Collectively, these research projects advance our understanding of influenza virus biology by leveraging cutting-edge imaging technologies to unravel key aspects of host-pathogen interactions
Photolysis of Emerging Agricultural Applications Under Environmental Conditions
No full textNovel agricultural applications are rapidly emerging to protect crops from weeds or pests in the US and worldwide. Isoxaflutole is a proherbicide considered agriculturally significant because it controls weeds that have developed resistance to other commonly used herbicides. In addition, RNA interference (RNAi) technology is regarded as a next-generation biopesticide because the technology has less toxicity to humans and more specificity to pests than traditional pesticides, which pose risks to the environment and the health of humans and livestock. However, we cannot disregard the possible risks of the emerging proherbicides and biopesticides to humans or non-target organisms. Therefore, the study of the environmental attenuation pathways (e.g., hydrolysis and photolysis) of these emerging agricultural applications is necessary to develop regulations and additional agricultural applications. The first objective examined the transformation of isoxaflutole and its active form, diketonitrile, via abiotic hydrolysis and photolysis at circumneutral pH, which are both key processes impacting the fate of these contaminants. Because isoxaflutole hydrolysis is triggered by hydroxide and buffer ions, the concentration of buffer salts was controlled to ensure that buffer salts hydrolysis did not significantly contribute to isoxaflutole hydrolysis at most pH values. Consequently, isoxaflutole hydrolyzes to diketonitrile with half-lives that are much longer than prior modeling suggested. After correcting for hydrolysis, I found that isoxaflutole photolyzed under simulated sunlight with a steady quantum yield in the buffers and surface waters, corresponding to a predicted near-surface half-life, which was also longer than previously suggested. Diketonitrile, which does not hydrolyze in all matrices, underwent slow photolysis despite significant absorbance within the solar spectrum, resulting in a much lower quantum yield than isoxaflutole quantum yield. To investigate the kinetics of isoxaflutole photolysis, I derived a model showing that diketonitrile was not a primary isoxaflutole photoproduct. Isoxaflutole photolysis generated several photoproducts, which showed different stabilities in the buffers at two pH values. The second objective examined the direct photolysis of dsRNA, the RNAi product, on glass and polytetrafluoroethylene (PTFE) surfaces, which represent the conditions of the leaf surface. The photolysis of dsRNA under simulated sunlight was accelerated by orders of magnitude when dsRNA was dried on surfaces as opposed to solution, when measured using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). I investigated the effect of the absorption of dried nucleic acid on the rapid surface photolysis and concluded that the dried dsRNA did not absorb more light on the surfaces than in solutions, suggesting that this accelerated photodegradation resulted from an increase in the photochemical quantum yield. To classify the photodamage of dsRNA, I analyzed dsRNA degradation using gel electrophoresis, indicating that photodegradation was not attributable to strand breaks. The rapid surface photolysis was more likely associated with photodegradation of nucleobases, resulting in accelerated loss of nucleoside monophosphates (NMPs) from digested dsRNA after its photodegradation on the glass surface compared to in solution. Overall, this study provides a comprehensive photochemical analysis of the emerging agricultural applications under environmental conditions. The photolysis of isoxaflutole and diketonitrile provides the clear kinetics and predicted half-lives of proherbicides under the environmental conditions. The unexpected photolysis behavior of dsRNA on the surfaces shows the importance of dsRNA photolysis in foliar application. This study indicates that the photolysis of the proherbicide and biopesticide is potentially comparable to the other environmental attenuation pathways considered in the prior environmental fate assessment
Moment Ensemble Approaches for Estimation and Robust Quantum Control
No full textLarge-scale population dynamics governed by ensemble systems present significant challenges due to their inherently high dimensionality. Recent advances have demonstrated the effectiveness of moment-based methods (particularly those employing polynomial bases such as Legendre and Chebyshev polynomials) when integrated with optimization techniques for control design in ensemble systems. However, these methods have not been extensively explored for enhancing robustness against systematic noise, nor have they been widely applied to complex quantum systems involving multi-parameter configurations and entanglement phenomena. In this work, we extend the application of moment methods in ensemble systems through two projects. Initially by developing a Kalman filter analogue, achieved through the decomposition of systematic stochastic processes into their corresponding moments. The resulting methodology enables sub-optimal noise filtering while significantly reducing computational cost via dimensionality reduction. Furthermore, we apply optimal Hamiltonian engineering to quantum systems characterized by parameterized inhomogeneities. Our first application involves the matter-wave splitting of a Bose-Einstein Condensate (BEC) under experimental imperfections and initial momentum dispersion, demonstrating increased fidelity and improved performance for quantum metrology. Additionally, we employ this approach in a quantum network of two-level systems (e.g. qubits, spin particles, ...) governed by the symmetric Ising model. These tensor-network-driven dynamics are simulated, and optimized pulse sequences are generated for the robust preparation of entangled symmetric states, including GHZ and W states, which are crucial for high-precision quantum sensing
Taking Small Steps With Big Data: Exploring the Impact of Education on Social Mobility
No full textHistorically, education and workforce-development programs have relied on survey data or state-government administrative data to examine program impacts. However, surveys are costly, reasonable comparison groups can be difficult to identify, and results from analyses of a single state’s administrative data can seldom be generalized to enable broader conclusions. This brief discusses a research collaboration between the Center for Social Development, the National Student Clearinghouse, and a large credit bureau. Through this collaboration researchers used large, frequently updated, multi-type (i.e., “big”) data to examine the impact of education and certificate programs on social mobility, as well as racial and gender equity.
This Practice Brief is the first in a series of case studies that highlight how social sector organizations are implementing collaborative and equitable data practices to increase their impact. The series promotes peer learning and knowledge sharing among social sector practitioners from diverse backgrounds, sectors, and roles
Integrating synaptic transistors with perovskite photodetectors for neuromorphic applications
No full textThe convergence of neuromorphic electronics and optoelectronic materials offers a pathway toward next-generation artificial vision systems. Synaptic transistors, which emulate the adaptive plasticity of biological synapses, can process information in an energy-efficient and parallel fashion. Perovskite photodetectors, on the other hand, provide tunable band gaps, high responsivity, and facile fabrication, making them excellent candidates for light sensing. Integrating these two device classes enables direct photoresponsive computation, where optical signals are not only detected but also weighted, filtered, and stored in a single element. My research explores the electrical and optical coupling mechanisms in such hybrid devices, examining how ion migration, trap states, and interfacial engineering affect synaptic behavior under illumination
Mapping Phosphorylated Tau using Multidimensional MRI in Alzheimer’s Disease
No full textINTRODUCTION: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that severely impairs memory and cognition, posing an increasing public health challenge worldwide. Current research suggests that AD is strongly linked to the abnormal accumulation of phosphorylated tau (pTau), a pathological hallmark reflecting neuronal dysfunction and neurodegeneration. Clinically, pTau is typically assessed via cerebrospinal fluid (CSF) analysis or tau positron emission tomography (tau-PET). Although informative, CSF analysis is invasive, and tau-PET requires ionizing radiation. Furthermore, tau-PET is limited in routine clinical settings due to its high cost and radiation exposure. There remains an urgent need for a non-invasive, safe, and widely applicable imaging method to characterize the spatial distribution and concentration of pTau in the human brain to support a biologically based diagnosis of AD.
METHODS: To address this need, this research proposes an imaging framework that integrates multidimensional MRI (MD-MRI) with supervised machine learning to estimate voxelwise pTau concentration and its spatial distribution. The approach leverages the rich microstructural information embedded in the voxelwise diffusion-relaxation probability distributions derived from MD-MRI. Eight postmortem human brain slices from four donors were analyzed. Voxelwise 2D joint distributions of T1, T2, and Mean Diffusivity (T1D and T2D) were derived from MD-MRI, and vectorized joint distributions were applied as input features. Histology-derived pTau concentrations and spatial distributions from the same samples, quantified via immunohistochemistry, served as the ground truth. pTau concentration was stratified into either 2 classes (high vs. low) or 3 classes (low, moderate, high) for subsequent classification. To comprehensively evaluate the framework’s effectiveness, multiple regression and classification models were employed to predict pTau concentration. Before model training, to eliminate the influence of imaging artifacts, only valid voxels within the region of interest were retained according to the binary mask. To simplify the data structure and improve computational efficiency, principal component analysis (PCA) with 95% threshold was applied for dimensionality reduction. During the training phase, a nested cross-validation (5 outer folds and 5 inner folds) was employed to assess model generalizability, while Bayesian optimization was used to select the optimal hyperparameters within each inner loop. For regression tasks, we compared linear regression, quadratic regression, support vector regression (SVR), random forest, and multilayer perceptron (MLP). For 2-class and 3-class classification tasks, we evaluated logistic regression, Fisher’s linear discriminant (FLD), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP).
RESULTS: The results demonstrated that the random forest model consistently achieved the best and most stable performance across all tasks. For regression, random forest achieved the lowest mean squared errors and highest goodness of fit for both T1D (MSE 0.031 ± 0.001, R2 = 0.797 ± 0.007) and T2D (MSE 0.040 ± 0.001, R2 = 0.724 ± 0.005). For 2-class classification, this model reached accuracies and Cohen’s kappa, respectively, of 0.924±0.002 and 0.803±0.001 for T1D, and 0.909±0.003 and 0.779±0.009 for T2D. For 3-class classification, the model achieved accuracies of 0.879 ± 0.004 for T1D and 0.858 ± 0.005 for T2D, with corresponding Cohen’s kappa values of 0.841 ± 0.004 for T1D and 0.820 ± 0.006 for T2D, respectively. These findings underscore the robustness of the random forest model. It consistently demonstrated superior
predictive capability across both regression and classification tasks. Importantly, the reconstructed imaging maps based on the coordinates of each voxel visually demonstrate a strong concordance between the model predictions and the histology-derived pTau distributions and concentrations, confirming the validity of the approach. Quantitatively, this agreement was confirmed by the structural similarity index measure (SSIM) analysis, with mean SSIM values of 0.82 and 0.81 for regression, 0.90 and 0.89 for binary classification, and 0.87 and 0.86 for 3-class classification on the T1D and T2D data, respectively.
DISCUSSION: These results demonstrate that the T1D and T2D diffusion–relaxation joint distributions of MD-MRI encode rich microstructural information related to tau pathology, and the random forest model can effectively capture this information to predict pTau concentration. The strong spatial correspondence and high SSIM values confirm that the reconstructed images reflect clinically meaningful and biologically relevant patterns of pTau accumulation.
CONCLUSION: Overall, this study establishes a proof of concept that MD-MRI–derived joint distributions can non-invasively capture tau pathology in Alzheimer’s disease. This framework may potentially provide a safe and non-invasive alternative to CSF analysis and tau-PET in clinical diagnosis. In the future, this approach may have potential clinical utility as a marker of tau pathology. Future work will extend this framework to in vivo human datasets to validate its clinical applicability