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Stimulus Dependence of Visually Guided Behavior in Drosophila Melanogaster
Get PDFVision is very important for navigating the world around us. The fruit fly, Drosophila melanogaster, is a great model for studying how the brain controls visually guided behavior. This is because they have a small nervous system, good genetic tools, and a complete map of their brain connections. In fruit flies, visual projection neurons (VPNs) send information from the eyes to the central brain, which affects what they see and how they act. This research looks at how certain groups of nerve cells influence fruit flies\u27 behavior based on what visual stimuli. To study the brain circuits behind these behaviors, I used genetic techniques to silence specific neurons. I targeted T4/T5 neurons, which are important for sensing motion and causing optomotor responses. I used tetanus toxin (TeNT). Initial tests showed strong optomotor responses in normal flies. However, blocking T4/T5 neurons with TeNT was lethal, suggesting these neurons are crucial for survival. I also studied how specific stimuli influence Drosophila behavior. I specifically focused on fixation (keeping their gaze steady) and optomotor responses (moving in response to visual motion). These are two key ways flies stabilize their view and stay oriented while moving. Using a special virtual reality setup, I looked at how changes in what they saw affected their walking and direction. I found that fixation responses were there, but weak, and when combined with optomotor stimuli, the optomotor response seemed to dominate fly behavior. Future work will use an exogenous expression of kir in T4/T5 neurons to carefully silence neurons and further explore how the brain controls behavior based on visual input. Overall, this project combines studying behavior with manipulating neurons to better understand how visual signals and specific brain cells work together to control attention and movement in fruit flies. This could also help us understand how sensory information is processed in more complex brains
The Role of Cis-acting Super-enhancer Long Noncoding RNAs in Triple Negative Breast Cancer Progression
Get PDFBreast cancer encompasses a diverse range of diseases characterized by the uncontrolled proliferation of cells within the mammary gland. This condition results in an accumulation of a large number of genetic mutations within an individual, altering the complex internal signaling system of a cell. Millions of women are affected by breast cancer, which remains a significant threat despite medical advancements. Ductal carcinoma in situ (DCIS) acts as a precursor to invasive ductal carcinoma (IDC), however, not all cases progress to invasive cancer. Triple-negative breast cancer (TNBC) is identified to be one aggressive subtype of IDC, where the cells lack sufficient levels of progesterone receptors, estrogen receptors, and HER2 proteins. According to numerous studies, super-enhancers not only promote gene transcription but also result in super-enhancer long noncoding RNAs (SE-lncRNA) by transcribing themselves, playing an important role in tumor progression. These SE-lncRNAs can interact with associated enhancer regions and influence the expression of neighboring genes. Even though DCIS does not always lead to breast cancer, the current approach to DCIS treatment remains an aggressive course of therapy, resulting in over-treatment. It is therefore essential to identify functional elements that drive the transition from DCIS to IDC, to differentiate the treatments for indolent and aggressive forms of the disease. Studying the role of these SE-lncRNAs can aid in advancing therapeutic techniques. Here, we knockdown two specific SE-lncRNAs, TFAP2A–AS1 and RP11-379F4.4 in the MCF10A-CA1 (CA1) cell line to observe its effect on its neighboring protein-coding genes, TFAP2A and RARRES1, respectively
From CUNY to Columbia: A Comparative Analysis of Student Movements at Private and Public Institutions
Get PDFIn this paper, I will argue that while student movements at Columbia were often able to achieve short-term institutional changes, in part due to the University’s flexibility to cede to their demands due to their status as a private institution, these wins often do not hold in the long term. While they may impact broader social conditions, the long term impact on political conditions is somewhat limited by the institution’s insular and elite nature. In contrast, student movements at CUNY, though often less able to affect immediate institutional reform due to financial constraints and bureaucratic resistance, had a more profound long-term influence on higher education public policy, particularly in the context of securing and improving access to higher education for marginalized communities. This analysis, which spans from the late 1960s to present day, will reveal how the specific characteristics of private and elite versus public and non-elite universities. Demographics, political engagement, institutional power, and resources all shape the efficacy of student activism and its broader implications for societal policy change
Unveiling the Cell Composition of the Olfactory Migratory Mass: Perspectives on Terminal Nerve Formation, Olfactory Development, and Migration of the GnRH-1 Neurons
Get PDFPuberty is a postnatal developmental process required to initiate key sexual maturation events that are necessary for the propagation of species. Signals to initiate these events first begin with the Gonadotropin releasing hormone-1 (GnRH-1) neurons within the hypothalamus. The hormone GnRH-1 released by these neurons is crucial for puberty, fertility and reproductive processes by establishing the hypothalamic-pituitary-gonadal (HPG) axis, regulating release of sex hormones (Progesterone, Estrogen, Testosterone). Conditions related to inability of the GnRH-1 neurons to correctly release GnRH-1 can lead to aberrant or delayed puberty, a condition known as hypogonadotropic hypogonadism (HH). Interestingly, some patients with the hormonal disorder seen in HH have been found to have impaired or no sense of smell, this classification is known as Kallmann syndrome (KS). The link between olfaction and puberty can be found during early embryonic development, the GnRH-1 neurons are not found within the brain and instead, the nose. The GnRH-1 neurons first arise within the olfactory placode (OP), migrating out of the nasal area to the brain as development progresses. How exactly the GnRH-1 neurons make this migration is still unknown. We believe that the GnRH-1 neurons are supported by a long forgotten and elusive structure known as the terminal nerve (TN) rather than olfactory neurons.
The TN is the only cranial nerve (XIII) known to project from the nose to basal forebrain. This is known from dissection studies over a century ago identifying the TN in various species such as sharks, fish, rodents and humans at both embryonic and adult stages. The characterization and function of the TN remains to be elucidated. My doctoral research aimed to learn more about TN development and its role in GnRH-1 migration. My second chapter highlights the first genetic lineage tracing experiments of the TN using the gene Prokineticin receptor 2 (Prokr2), a gene that has been found to have mutations associated with KS. We discovered that the GnRH-1 neurons and TN neurons are two distinct structures that closely associate, and that the neurons of the TN may be pioneer neurons, which initiate olfactory bulb morphogenesis. Additionally, we performed the first single-cell RNA sequencing of the TN, acquiring the first transcriptomic data of the TN. 26 genes associated with HH/KS were enriched in the TN sequencing data. In chapter 3, I discuss my work characterizing knockout mice for Fezf1, an important transcription factor in the correct differentiation of the olfactory neurons. We described the adverse effects to overall olfactory system development, and defects in the migratory mass, including reduced olfactory ensheathing cells (OECs), glial cells that support the GnRH-1 and TN neurons during their migration. Finally, in chapter 4, I describe my work on mice with mutations for Gli3, an effector in the Sonic Hedgehog (Shh) signaling and a critical molecule in OEC development. We acquired the first single-cell sequencing for two mutants of Gli3, Gli3XT/XT knockouts and Gli3PDN/PDN hypomorphs, and illustrated the dose-dependent effects of Gli3 on the development of the olfactory system at both the tissue and molecular level. This work uncovers developmental aspects of the TN, to gain a better understanding of its role in GnRH-1 migration and KS
Development of DNA Nanoswitches with Aptamer Based Detection for Thrombin
No full textBio-transducers are devices capable of converting the binding signals from molecular recognition events into readable signals for analytical detection. There is a need for modular bio-transducers that can specifically detect a wide range of analytes using a unified readout technique, as this approach could dramatically reduce costs of healthcare diagnostics and environmental monitoring.
To create such a modular transducer, the molecular recognition properties of aptamers will be used and integrated with the already established biosensing capabilities of DNA nanoswitches that reconfigure their shape in the presence of their target molecule. In this design, the detector strands of the nanoswitch will be made up of aptamer sequences, and thrombin will be the target molecule. Using this design of the nanoswitch successful binding of thrombin to the aptamer strands on the nanoswitch was observed. Various optimization methods were performed to determine the ideal conditions for aptamer folding and target binding producing a clear distinct signal on the agarose gel. To retrieve a clear signal on the agarose gel it was determined that it was important to include NaCl2, KCl, MgCl2, and CaCl2 into the sample prep, running conditions, and gel construction. Thrombin concentrations as low as 0.0187nM were detected using the developed nanoswitch. The specificity of the nanoswitch to thrombin was also tested by introducing 0.1mg/mL BSA, which proved that the nanoswitch only formed its looped conformation when thrombin was present.
This work will broaden the diversity of molecules that can be sensed with DNA nanoswitches and provide valuable information on the limit of detection of the aptamers used in the nanoswitch since aptamers are known to be weak binders compared to a DNA structure
Association of Non-communicable Diseases with Severe COVID-19 among People Living with and without Diagnosed HIV/AIDS in New York State
Get PDFBackground: People living with diagnosed HIV (PLWDH) have a higher chance of co-infections and co-morbidities than the general population. When SARS-CoV-2 was first reported in China in December 2019 and later declared a pandemic, it was speculated that PLWDH might be more prone to SARS-CoV-2 infection and severe disease outcomes given their increased vulnerability to other respiratory infections like influenza, pneumococcal pneumonia and tuberculosis. However, several facets of COVID-19 disease in PLWDH are incompletely understood, including whether non-communicable diseases (NCDs) are strong risk factors for severe disease outcomes and death as they are in the general population.
Methods: The data for my doctoral dissertation were collected by the New York State COVID-19 diagnosis and hospitalization study for PLWDH, which procured data from the Electronic Clinical Laboratory Reporting System (ECLRS), the Health Information Exchange (HIE), manual electronic medical record (EMR) reviews, and the New York State Electronic HIV Management System (NYEHMS). Statistical methods included survival analyses using Cox proportional hazards regression models in which hazard ratios were calculated for associations of NCD’s with death, intensive care unit (ICU) admission and mechanical ventilation among the PLWDH and people living without HIV who were hospitalized for COVID-19 during March 10, 2020, through June 6, 2020. The association between the main exposure and the outcomes were adjusted for age, sex at birth, race/ethnicity, smoking status and alcohol consumption.
Results: PLWDH had a higher prevalence of cardiovascular disease and renal disease, whereas people without diagnosed HIV had a higher prevalence of hypertension, diabetes mellitus and obesity and overweight. None of the NCDs was significantly associated with death, ICU admission or mechanical ventilation among PLWDH. Among people without HIV, diabetes mellitus was significantly associated with death, but not with ICU admission or mechanical ventilation. There was no interaction observed between NCD’s and HIV status, age and sex of the study population in the whole sample, and CD4 count, viral suppression and receipt of anti-retroviral therapy and outcome in PLWDH group.
Conclusion: In this analysis, PLWDH with select NCD’s did not have a higher risk or had a similar risk for mortality, requiring ICU admission or mechanical ventilation due to COVID-19 in comparison with people without HIV/AIDS and COVID-19. This could be plausible as PLWDH in this sample could have been regular in the care cascade for receiving services related to HIV/AIDS, which is seen in the form of majority of PLWDH been receipt of ARV, maintaining a CD4 count \u3e200 and virally suppressed. With more studies on COVID-19 among PLWDH happening across the globe, much new evidence on associations of NCD’s and severe outcomes related to COVID-19 will be available in the future
The Intermediate and Remote Effects of Acute Juvenile Stress upon Auditory Fear Learning, Recognition Memory, and Anxiety Measures in a Rodent Model of PTSD
Get PDFAbstract
Early-life stress is a risk factor for increased susceptibility to stress- and trauma-related disorders, including Posttraumatic Stress Disorder (PTSD). PTSD is characterized by exposure to trauma that results in exaggerated and extinction-resistant fear responses that persist for over a month. Understanding how the severity of early-life stressors in animal models impacts adult behavior, cognition, and underlying neurobiology could aid in the development of more effective PTSD treatments.
Various early-life stress models, especially in infant rats, have been used to induce stress and assess PTSD like-symptoms. Different stressors impact short- and long-term behavior, with some effects influenced by developmental timing of exposure. Most studies focus on the pre-weaning period, leaving post-weanling juveniles largely understudied. The juvenile period is a critical phase of neurodevelopment, during which stress-related plasticity differs from that of infancy or adulthood. Understanding stress effects during this stage could improve PTSD developmental models. However, it\u27s still unclear if different stressors cause similar or distinct short- and long-term impacts on cognition, fear, and anxiety. A framework explaining how different stress protocols affect assessed behaviors could enhance research on stress- and trauma-related disorders.
Stress during infancy is well known to alter both immediate and long-term affect and learning processes. Investigating the effects of different juvenile stressors across recent and remote time points on anxiety, recognition memory, and auditory fear learning provides insight into how distinct stressors shape rodent anxiety, cognition, and their biological underpinnings. In Chapter 1, I provide background information on fear learning, memory, stress, and adolescence. Chapter 2 validates a weight-based scaling approach for adapting the novel object recognition (NOR) test, initially designed for adults, to juvenile animals. I then examine how different types and intensities of juvenile stress affect intermediate (Chapter 3) and remote (Chapter 4) anxiety, recognition memory, and cued-fear learning. I hypothesized that juvenile stress exposure would lead to both recent (6 days) and remote (66 days) alterations in anxiety and fear learning, that these changes would increase with stress intensity, and that females would exhibit more severe, sustained, long-term effects.
These experiments suggest that footshock stress provides a more robust and controllable stress induction model of PTSD than restraint stress. Furthermore, they offer insight into the ontogeny of PTSD by identifying key phases of the Stress-Enhanced Fear Learning (SEFL) model at different time points: the initial SEFL trial induces dynamic changes in cognition and arousal, which, in turn, enhance fear learning and expression in response to future aversive stimuli. Most importantly, these studies reveal long-term—but not short-term—enhancement of auditory fear learning following juvenile stress exposure using the SEFL model, extending our understanding of how stress impacts fear learning behavior and development. Together, these findings contribute to a more integrative framework for characterizing stressor-specific PTSD-related mechanisms across developmental stages
Evaluating the Use of the Floristic Quality Assessment Method in Comparing Ecosystem Health of Freshwater Lakes Treated with and without Copper-Based Pesticides
No full textThis study evaluated the use of the Floristic Quality Assessment (FQA) Method in assessing the impacts of copper-based pesticide treatment on lakes within the Hudson River Watershed of New York State (NYS). FQA is a vegetation-based ecological assessment method accounting for native and total species richness using Coefficients of Conservatism (C values) indicative of a plant species reliance on higher quality habitat and ecosystem processes, and overall tolerance to degradation. Greater FQA values correlate with higher quality vegetative communities and an associated increase in ecosystem health. Results derived from the FQA Method were used to analyze the health of 19 freshwater lakes distributed across two study groups (8 lakes with a history of copper-based pesticide treatment and 11 lakes with no historical record of treatment) and subsequently determine the viability of the FQA Method in assessing habitat degradation through comparison with results from a related study comparing copper concentrations in littoral sediment of lakes with and without a history of copper-based pesticide treatment. Past studies using the FQA Method have been limited to the state-level however this study also utilized ecoregional C values, thus the difference in results associated with a variation in C values between datasets was also investigated. Greater FQA values for both the NYS and Ecoregion dataset generally correlated with lower copper concentrations in littoral sediment of lakes, suggesting that the FQA Method is a viable indicator of habitat degradation and useful assessment tool for lake management. Furthermore, lakes treated with copper-based pesticides generally had lower FQA values in comparison to lakes with no record of treatment. No statistically significant (p value ≤ 0.05) difference in results between datasets was observed however Native Mean C (p value = 0.10) neared significance and was determined to be the metric most sensitive to ecological change
From Images to Insights: Machine Learning Enhanced Spectral Imaging for Dissecting Microbiome Spatial Structure
No full textAdvances in imaging technologies and computational tools are transforming our understanding of the spatial organization of microbial communities within the host. Here, we investigated the spatial structure of the gut microbiome and its functional relationship with host mucus phenotypes by integrating high-resolution imaging, machine learning-based spectral unmixing, and gnotobiotic zebrafish models to uncover the mechanistic principles underlying host–microbe interactions. We first reviewed recent developments in microbiome spatial ecology, highlighting two distinct yet complementary dimensions of spatial structure: biogeography, the distribution of microbes across anatomical regions, and architecture, their fine-scale organization within a niche. This framework underscores how spatial context governs microbial community function and host interaction.
Using axenic, conventional, and gnotobiotic zebrafish models, we found that specific microbial taxa, rather than total bacterial biomass, drive mucus abundance and spatial patterning in a tissue- and context-dependent manner. For example, colonization with a defined bacterial consortium was sufficient to restore mucus production and gut architecture in axenic fish, recapitulating conventional phenotypes despite variation in overall microbial load—supporting the concept of microbial functional sufficiency. However, we also observed inherent variability in colonization outcomes and host responses across gnotobiotic individuals, highlighting a limitation of current re-conventionalization approaches. These findings reinforce the need to validate microbial colonization in gnotobiotic experiments to improve reproducibility and biological interpretation in host–microbiota studies.
Building on this framework, we addressed a major technical challenge in microbial imaging: resolving species-level identity in densely labeled, multiplexed communities. To overcome the resolution limitations of conventional fluorescence imaging and 16S rRNA-based methods, we developed, Cross-hybridization Inference and Phylogenetic Resolution fluorescence in-situ hybridization (CIPHR-FISH), a novel machine learning-based spectral classification framework for species-level identification in multiplex-labeled microbial communities. This approach was developed to test our functional sufficiency hypothesis more directly by enabling species-level resolution of microbial spatial patterns and identifying core microbiota configurations associated with differential host outcomes. This method generates and captures ‘cross hybridization inference’ that capture excitation/emission properties, spectral cross talk and probe cross-reactivity, enabling pixel-level classification of microbial species. Applied to a synthetic zebrafish gut consortium, the framework achieved 100% specificity and high sensitivity, surpassing traditional linear unmixing techniques and setting a new benchmark for microbial imaging. We then applied this high-resolution image analysis pipeline to examine microbial identity and spatial organization in vivo in the zebrafish gut and identified Aeromonas sp. as the dominant taxon in the presence of 5 other co-colonizing taxa—consistent with 16S rRNA sequencing data from these communities.
Altogether, this work integrates microbiome imaging, machine learning, and host physiology and development to reveal how microbial spatial structure shapes host mucosal environments, advancing tools our ability to map, resolve, and interpret microbiota–host relationships with unprecedented resolution
Safeguard Cyberspace in Ransomware Era: Risk Analysis & Cyber Insurance
No full textThe increasing frequency and severity of ransomware attacks pose significant challenges for organizational cybersecurity. Fragmentation across disciplines in cyber defense has created practical gaps in the development of the necessary capabilities needed to address rapidly evolving cyber threats. This study explores the impact of ransomware attacks and the evolving role of cyber insurance as a proactive cybersecurity partner. Bridging the gap between actuarial science and cyber risk management, it proposes an interdisciplinary framework that quantifies the impact of ransomware and integrates cyber insurance into cybersecurity strategies.
The primary contribution of this study is methodology. We present a framework that remains applicable and adaptable as more recent ransomware incident data becomes available. Future researchers can use this framework to analyze the fast evolving ransomware risks and mitigation strategies.
Drawing on a filtered dataset of ransomware incidents from the Advisen Cyber Loss Database (2018–2020), the study employs a generalized linear model (GLM) with Gamma regression to examine the impact of vulnerability, technology, settlement length, and external connection on expected financial losses. Bootstrapping is used to assess the robustness of a model. Findings reveal that these socio-technical factors significantly shape the severity of ransomware losses, highlighting the importance of carefully designed mitigation strategies.
The research further develops a matrix-based framework aligned with the NIST Cybersecurity Framework, mapping pre-incident and post-incident cyber insurance services to each of the five risk management functions (Identify, Protect, Detect, Respond, and Recover). This integration highlights cyber insurance as a provider of expert services that enhance resilience and reduce vulnerability for organizations.
This study contributes to both theory and practice by providing a quantitative basis for ransomware risk assessment and offering valuable insights into the potential of cyber insurance as an integral component of cybersecurity governance. It concludes with policy and managerial recommendations, outlining future research directions that involve AI-enhanced risk modeling and qualitative investigations of organizational dynamics in ransomware response