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Plasma phospho-tau217 as a predictive biomarker for Alzheimer’s disease in a large south American cohort
Get PDFBackground
Blood-based Alzheimer’s disease (AD) biomarkers have been increasingly employed for diagnostic, prognostic, and therapeutic monitoring purposes, due to accuracy in distinguishing AD pathophysiologic process. Compared to other p-tau isoforms, plasma p-tau217 exhibits stronger associations with AD hallmarks in CSF and brain. However, most studies have been conducted in non-Hispanic Whites, limiting our understanding of the performances and utility of these biomarkers across ethnicities.
Methods
We examined a cohort of Peruvians from the GAPP study, a recently established cohort of Peruvian mestizos from Lima and indigenous groups from Southern Peru (Aymaras and Quechuas). We tested plasma levels of p-tau using the Quanterix Simoa ALZpathp-tau217 assay in 525 samples and tested the association between p-tau217 and clinical diagnosis (healthy controls n = 234 vs. AD n = 113) using generalized mixed regression models, adjusting for sex, age, education, APOE-e4 allele (fixed effects) and study site (random effect). We also tested biomarker levels in MCI (n = 178) vs. other groups. The receiver operating characteristics area under the curve (ROC-AUC) was used to evaluate the biomarker’s classification performances.
Result
Participants showed on average 80% Native American ancestry. p-tau217 was significantly associated with AD (β = 2.61, 95%CI = 0.61–4.29) and its levels were inversely correlated with cognitive performances; p-tau217 levels did not differ between controls and MCI (p-value > 0.05). p-tau217 levels were higher in participants carrying at least one APOE-e4 allele (OR = 2.31, 95%CI = 1.85–2.90). The ROC-AUC for p-tau217 was estimated at 82.82% in the fully adjusted model.
Conclusion
To our knowledge, this is the largest study conducted in a South American cohort phenotyped for AD with available p-tau217. Most investigations have previously focused on highly selected cohorts with established AD-endophenotypes (CSF biomarkers, autopsy report, PET etc.), while data on cohorts with clinical assessment are currently lacking, especially in non-European populations
The Role of Cardiovascular Morbidity in the Relationship between Ambient Air Pollution Exposure and Adverse COVID-19 Outcomes
No full textThe COVID-19 pandemic elucidated geographical disparities in COVID-19 burden on a globalscale. Geographical disparities in adverse COVID-19 outcomes may suggest population-level drivers of disease, such as environmental exposures. Epidemiological literature provides strong evidence that greater exposure to ambient air pollution, an environmental exposure, is associated with a greater risk of COVID-19 hospitalization and fatality. The pathways by which ambient air pollution exposure influences adverse COVID-19 outcomes are currently unknown. I propose that cardiovascular morbidity is relevant in this pathway, given that cardiovascular morbidity is a predominant risk factor of adverse COVID-19 outcomes, and there are strong and consistent associations between air pollution and cardiovascular morbidity. I suggest that the role of cardiovascular morbidity will be different for historical air pollution (period > 30 days) and short-term air pollution (period < 30 days). By proposing clear causal structures for the relationship between air pollution and adverse COVID-19 outcomes, we can explicate how air pollution leads to greater COVID-19 burden and address the larger goal of reducing geographic disparities in adverse COVID-19 outcomes.
This dissertation is comprised of three specific aims. For the first aim, I performed a systematic review of the literature that examined the relationship between ambient air pollution and individual-level adverse COVID-19 outcomes. I identified if and how researchers conceptualized the causal role of comorbidities, specifically cardiovascular morbidities, in the relationship between air pollution and adverse COVID-19 outcomes. For the second aim, I examined if cardiovascular morbidity mediates the relationship between historical air pollution and adverse COVID-19 outcomes. For the third aim, I examined if there was evidence of synergistic interaction between short-term air pollution and cardiovascular morbidity in influencing the risk of adverse COVID-19 outcomes, suggesting that the effect of both short-term air pollution and cardiovascular morbidity on adverse COVID-19 is greater than the sum of the individual effects.
In conducting the first aim, I used Covidence, a software used to manage systematic reviewstudies, to identify studies that examined the relationship between ambient air pollution exposure and individual-level adverse COVID-19, using the Embase, MEDLINE, and Web of Science databases. In conducting the empirical aims, I used a retrospective cohort study design using INSIGHT-Clinical Research Network (CRN) data, a harmonized repository of inpatient electronic health records in New York City (NYC) across metropolitan healthcare systems (3/1/2020-2/28/2021). INSIGHT-CRN included data pertaining to sociodemographics, diagnoses, outcomes, and residential ZIP Code to link air pollution exposure.
For the second aim, I used the New York City Community Air Survey (NYCCAS) to estimate historical air pollution exposure to particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO₂), and ozone (O₃) on a ZIP Code level (2009-2019). For the third aim, I used the 2020 Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) downscaler modeled data, which estimated 2020 daily exposure to PM2.5 and O3 on a census tract level. I aggregated the census tract data to ZIP Code using a spatial weighting approach and estimated short-term air pollution as a 7-day average of daily PM2.5 and O3 exposure prior to patient hospitalization.
For the first aim, the systematic review included 42 studies that examined the relationship between ambient air pollution, such as exposures to PM2.5, NO₂, and O₃, and individual-level adverse COVID-19, such as hospitalization, intensive care unit (ICU) admission, intensive respiratory support (IRS), and fatality. The studies were primarily retrospective cohort study designs, and were conducted in the United States and Europe (2020 to 2021). The majority of studies adjusted for cardiovascular morbidity without causal role specification, whereas some studies identified cardiovascular morbidity as a mediator or an effect modifier.
For the second aim, I found evidence of cardiovascular morbidity mediating the relationship between historical air pollution and risk of acute respiratory distress syndrome (ARDS), dialysis use, ventilation use, and COVID-19 fatality, but not risk of pneumonia from March to June 2020, within areas of greater hospital catchment. Indirect effects suggest that historical air pollution increases the risk of atrial fibrillation and myocardial infarction, which increases risk of adverse COVID-19.
For the third aim, I found evidence of synergistic interaction between short-term PM2.5 and presence of cardiovascular morbidities for only risk of COVID-19 pneumonia, in the latter half of 2020. Overall, there was evidence that cardiovascular morbidity mediates the relationship betweenhistorical air pollution and more severe COVID-19 outcomes, while cardiovascular morbidity synergistically interacts with short-term air pollution for risk of acute respiratory infections, such as pneumonia. This dissertation assesses the pathways by which air pollution may influence risk of adverse COVID-19, in better examining the causal role of cardiovascular morbidity. Knowledge gained could be used to mitigate population-level vulnerabilities to air pollution, and encourage population-level pandemic preparedness in the future
Investigating the impact of site-specific replication stress on homologous recombination
Get PDFGenomic instability is a hallmark of cancer that can be caused by various forms of DNA replication stress. Collision of the replication fork with obstacles ahead of the replication machinery can result in replication fork stalling and collapse. To overcome or bypass these obstacles and resume proper replication fork progression, the cell has various replication restart mechanisms involving homologous recombination (HR) that help preserve genome integrity and ensure cell survival. However, HR can also lead to genome rearrangements, particularly when recombination occurs between repetitive DNA sequences. The tandem duplicator phenotype found in breast and ovarian cancer is an example of a genome-wide instability configuration that has been associated with pathways related to homologous recombination and replication stress, but the exact mechanism of how these duplicated sequences are formed is not fully understood.
To examine the molecular mechanisms regulating genome instability in response to replication stress, we have established a genetic system in Saccharomyces cerevisiae to detect recombination events that result in tandem duplications (TDs) and deletions. Using this system, we investigated the mechanisms of recombination upon site-specific replication fork stalling initiated by a protein-induced replication fork barrier. We have found that a Tus/Ter-induced fork block downstream of direct repeats results in an induction in recombination events resulting in TDs and deletions compared to spontaneous frequencies, and that these recombination events have specific genetic requirements.
Mainly focusing on the recombination mechanisms generating Tus/Ter-induced TDs, we determined that formation of these TDs is dependent on Rad52, Rad51, the Mph1 translocase, and structure-selective endonucleases, and that these events appear to be enhanced by disruption of the MRX complex and sister chromatid cohesion. We also found that genetic requirements for recombination in response to fork stalling by a protein-DNA barrier are distinct from those involved in fork collapse at a nick. Taken together, these studies give insight into the mechanisms governing copy number variation in the context of replication fork stalling, which may ultimately provide a better understanding of how replication stress contributes to cancer and other diseases characterized by genome instability
Mathematical Modeling and Data-Driven Analysis of Embryo Development
Get PDFEmbryo development is a highly coordinated process where genetic regulation and mechanical forces interplay to drive the transformation of a single cell into a complex, multicellular organism. It involves many fundamental processes such as cell division, cell differentiation, and morphogenesis. Morphogenesis, the shape changes of tissue, results from collective cell movement, growth, proliferation, and shape changes, guided by genetic and mechanical cues. Despite the comprehensive data obtained from experimental measurements and advanced imaging, the physical mechanisms underlying morphogenesis are poorly understood, a quantitative cell shape pattern that describes morphogenesis has yet to be discovered, and the coupling between cytoskeleton that generates stress and shape changes has not been quantitatively demonstrated.
To address these unsolved questions, we utilized a powerful combination of first-principles modeling and empirical, data-driven approaches. Chapter 1 presents our mathematical model of Drosophila ventral furrow formation, which incorporates actomyosin contractile stress and viscous tissue responses. With all model parameters fitted from experiment, our model quantitatively explained numerous experimental observations in wild-type and genetically perturbed embryos, which were not fully explained by other models assuming elastic tissue responses. Our model revealed that the tissue-scale contraction in ventral furrow formation is driven by the curvature of the multicellular myosin profile. We also demonstrated that the pulsatile time-dependence of myosin acts as a protective mechanism for tissue contraction, suppressing cell-to-cell myosin fluctuations through a low-pass filter effect. This is crucial because tissue contraction is highly sensitive to even small myosin fluctuations, which would otherwise lead to significant inhomogeneous contractions.
Chapter 2 details our data-driven approach to studying Drosophila ventral furrow formation, utilizing time-lapse 3D data from light sheet microscopy. We developed computational algorithms to systematically parameterize over 28,000 cell shapes, designed interpretable cell shape features, and employed unsupervised learning to classify cell shape evolution trajectories. By mapping these classes onto the embryo, we extracted the first quantitative cell shape pattern in the Drosophila embryo. This pattern unveiled key physical mechanisms underlying embryo development, including how mechanical stresses propagate, how cell packing is influenced by embryo curvature, and the stochastic nature of apical constriction during tissue contraction.
Chapter 3 explores the coupling between actomyosin density and shape changes. We developed a mathematical model of the actomyosin cortex, using partial differential equations to describe the evolution of actomyosin density on a deformable surface, which is represented through differential geometry. Our model revealed that although under physiological conditions, the cell cortex is observed to maintain a homogeneous density and shape, this stability is challenged by two factors: increased cortical tension, which is mechanical in nature, and an elongated aspect ratio, which is a geometric feature. Higher cortical tension disrupts this homogeneity, leading to patterned actomyosin density and multiply furrowed shape. In contrast, an elongated aspect ratio drives constriction through a mechanism we named active Rayleigh instability, a modified form of the Plateau-Rayleigh instability. Furthermore, friction plays a crucial role in protecting the homogeneous state by preserving a large region of homogeneity in the state diagram of the cortex. When friction is reduced, this homogeneous region shrinks significantly, making the cortex more vulnerable to destabilization caused by increased tension and an elongated aspect ratio
Multi-Proxy Paleoceanographic Reconstructions of the Late Pleistocene Eastern Equatorial Pacific
No full textThe equatorial Pacific is a dynamic region, characterized by zonal and meridional asymmetries in both the ocean and the atmosphere. The asymmetries in the eastern equatorial Pacific (EEP) reach a maximum in northern hemisphere fall, when southern hemisphere trade winds cross the equator and drive the upwelling of cold, CO₂ and nutrient-rich waters along a shallow thermocline, fueling marine primary production. Interannual perturbations in ocean heat content also result in El Niño or La Niña events, which diminish or amplify these asymmetries.
In this dissertation, multi-proxy paleo-records derived from marine sediment cores are used to reconstruct fundamental aspects of the coupled ocean-atmosphere system in the EEP and to evaluate the hypothesis that changes in the seasonal distribution of equatorial insolation, which were primarily controlled by Earth’s precession, influenced the mean state and variability of the EEP in the late Pleistocene. EEP thermocline depth, reconstructed from the δ18O of multiple species of planktic foraminifera that lived at different depths in the water column, was found to oscillate between a La Niña-like and an El Niño-like state on precession timescales, in close phase with equatorial insolation during northern hemisphere late summer/early fall. EEP export production, reflected in sedimentary 231Pa/230Th, was influenced by changes in high latitude nutrient leakage and upwelling and, at times, varied on precession timescales.
Glacial increases in EEP deep ocean carbon storage, reconstructed from sedimentary authigenic 238U, occurred independently of changes in local export production. Individual δ18O analyses of the surface-dwelling foraminifera Globigerinoides ruber were used to reconstruct EEP sea-surface variability during the last interglacial and penultimate glacial period. While sea-surface variance was not significantly different from that of the late Holocene, the paleo-record suggests that the strength and frequency of ENSO events varied with changes in equatorial insolation during northern hemisphere late summer/early fall and with EEP thermocline depth
Sensing and Treatment Modalities Toward a Closed-Loop Wound Healing System
No full textChronic wounds pose a major threat to healthcare systems, and can be caused by a variety of factors, from diabetes to battlefield injuries. Traditional wound care does not account for a patient’s specific circumstances, and is only effective in up to 50% of cases. As such, there is a growing need for smarter wound healing technologies that can be used in a wide array of settings, from low resource hospitals to at home, and that provide customized treatments that can be administered without trained professionals. In this dissertation, we detail the development of technologies for customized treatments to accelerate wound healing.
In Aim 1, we used a water-activated, electronics-free dressing to accelerate wound healing in a diabetic mouse model. Electrical stimulation has previously been used to improve wound healing; however, common dressings often require that the wearer be physically connected to large benchtop electronics, are expensive to produce, and/or contain toxic elements. We demonstrated that this device, developed by our collaborators, accelerated time to wound closure by approximately 30%, on par with other, more complex devices, and further improved angiogenesis, collagen intensity, and reduced inflammation when compared with the controls. Furthermore, we demonstrated that this device is biocompatible and does not affect mouse behavior; the device does not heat up when activated, and did not impact the distance the mice traveled during a ten-minute measurement window. We are exploring additional use cases for this technology to further accelerate wound healing, including through iontophoresis, the use of electric currents to transmit drugs through the skin.
In Aim 2, we developed ultrasound-responsive, perfluorocarbon-based nanoparticles for spatiotemporal control of payload release. Focused ultrasound can be used to selectively and noninvasively trigger perfluorocarbon vaporization, releasing the payload from the triggered nanoparticles without disrupting nearby nanoparticles. Furthermore, these systems can be designed to remain stable when not in use, and to then release their payloads at safe acoustic pressures. We developed PLGA-coated, perfluorocarbon-based nanoparticles of various sizes, geometries, and with payloads. We used B-mode imaging and acoustic signal analysis to determine the acoustic thresholds of these nanoparticles, and then incorporated the nanoparticles into gels, from which we measured their payload release upon exposure to focused ultrasound. Initial in vivo testing of these nanoparticles showed that they remained stable until application of focused ultrasound. Such a technology has the potential to customize healing treatments, releasing specific payloads when and where they are most needed.
In Aim 3, we integrated components of a closed-loop wound healing system in vitro and in vivo. This system comprises an ultrasound bandage to provide both sensing of the wound and treatment to the wound, sensors to analyze the wound state, drug delivery depots to selectively release payload into the wound, and a machine learning algorithm to guide treatment based on sensor values. We developed ultrasound-responsive microcapsules to selectively release drugs, and tested these in vitro and in a diabetic mouse wound model. We tested the ultrasound-responsiveness of alginate-acrylamide hydrogels in vitro and in vivo. We additionally tested versions of the ultrasound bandage and lactate sensors in vivo, and tested various combinations of these technologies. We tested the release of growth factor from the hydrogels using focused ultrasound while collecting ultrasound images for analysis, and demonstrated that a commercial-grade ultrasound probe can differentiate between wound healing states, which suggests that this technology will be translatable beyond the lab. Future work could demonstrate a truly closed-loop system, and could move beyond the diabetic mouse model, to one more similar to healing in humans.
In this dissertation, we demonstrated technologies that can, individually or together, be used to improve wound healing in a variety of settings. Overall, this work advances the field of wound healing and demonstrates a suite of tools that can be used to provide customized treatments based on a patient’s needs, towards a vision for closed-loop wound healing systems
“From the Workshop to Lomonosov’s Laboratory: Chymical Knowledge in Early Modern Russia (1500-1800).”
No full textThe dissertation focuses on the history of Russian chemistry between the sixteenth and eighteenth centuries. Present scholarship contends that the growth and maturation of chemistry in Russia was a straitlaced process, state imposed and directed, and critically tied to the founding of the Imperial Academy of Sciences in St. Petersburg (1724-1725). Within this generally accepted school of thought, the infrastructure, codes of conduct, and ways of thinking that are the precursors of a vibrant chemical culture had no precedent in Russia, and historians portray them as having sprung up overnight by the founding of this institution.
This dissertation refutes this seemingly immaculate conception of chemistry on Russia soil. Through a detailed examination of primary sources, including manuscript collections of artisanal recipes, legal contracts, tsarist decrees and acts (Polnoe Sobranie Zakonov), canon codes (Stoglav), synodal correspondence, printed annual calendars (Kalendar' ili Mesiatsoslov Khristianskii) and almanacs (Brius Calendars), as well as academic papers, chemical journals, public lectures, odes, correspondence, and artifacts of Mikhail Vasil'evich Lomonosov (1711-1765), this study details how chemical practices, practitioners, and ideas across a multiplicity of sites grew, diversified, and entered the scholarly and courtly domains in the course of the eighteenth century in Russia.
By uncovering a vibrant chemical culture that existed before the founding of the Imperial Academy of Sciences and continued to thrive alongside it, this dissertation shows not only that Early Modern Russia hosted a robust knowledge-generating culture, but also that practical chemistry was endemic to Russia’s material and cultural landscape. In doing so, it lays to rest the enduring but erroneous scholarly assumption that the natural sciences, including chemistry, had no indigenous roots in Russia and were forcibly and belatedly transplanted onto Russian soil only in the eighteenth century. Such assertions imply that Russia was not only a docile recipient of scientific disciplines and thus played no role in their formation but also that scientific disciplines arrived on Russian shores as fully mature sciences with stable disciplinary identities and practices agreed upon by an international community of practitioners.
This dissertation makes two central claims. First, it argues that the entry of chemistry into the Academy was a dynamic process, negotiated by a confluence of actors, historical contingencies, and private interests, and not imposed by the state from above. To do so, it broadens the category of “science” and “scientific” to include pre-industrial processes and technologies, while outlining the essential preconditions for the development of a scientific culture. Second, it underscores the centrality of projects and projecting strategies to the crystallization of Russia’s popular scientific culture and discourse, and the development of chemistry as an academic discipline and a courtly science. This forces us to look at projecting not only as a hobbyhorse of adventurers, parvenus, and profit-seekers, but as a meaningful and epistemologically generative activity. In the middle of the eighteenth century, there were still many ways of doing academic chemistry, including Lomonosov’s Wolffian synthesis of “Physical Chymistry” (chymiae physicae or физическая химия), which had crystallized in the course of his projecting. Despite being grounded in corpuscular philosophy, Lomonosov’s “Physical Chymistry” offered a promising experimental framework for the study of chemical principles (first order constituents of mixed bodies), which was still mostly considered beyond the reach of chymical inquiry
Sustainable Digital Scholarship: Lessons from the Columbia University Libraries Podcast Publishing Initiative
No full textBeginning a new library publishing program is an exciting and challenging proposition. At the start of any program, sustainability must be integrated into program planning. In this chapter we will share information about the technical infrastructure used to launch, maintain, and preserve a podcast publishing program in an academic library setting, from within a digital scholarship unit. We will also expound upon our decision-making rationale and include discussion about how the workflows we utilized or developed can be and have been used in the management of other electronic scholarly publishing programs offered by the Columbia University Libraries (CUL)
Pristine Gold-Tape Exfoliation of Transition Metal Dichalcogenide Monolayers
No full textTransition metal dichalcogenides (TMD) monolayers have proven to be a premier class of two-dimensional semiconductor due to their chemical simplicity, suitable carrier mobilities, and desirable band gaps. However, popular fabrication methods fail to produce TMD monolayers with both suitable sizes and quality. The metal-assisted “gold-tape” method enables the deterministic exfoliation of macroscopic TMD monolayers from bulk single crystals, overcoming the size limitations of the widely used “Scotch-tape” method.
However, concerns regarding the quality of gold-exfoliated TMD monolayers have limited the technique’s adoption. This thesis discusses the quality and cleanliness of gold-tape exfoliated TMD monolayers from furnace to device. A substantial population of free charges is observed for photoexcited TMD monolayers, unless exfoliated from state-of-the-art flux grown crystals, highlighting the importance of parent crystal quality.
Furthermore, the discovery of a previously unknown irreversibly adsorbed polyvinylpyrrolidone (PVP) residue layer is chronicled, and a critical Ar/O2 reactive ion etch (RIE) step is introduced to eliminate it. Gold-tape exfoliation is shown to produce pristine, millimeter-scale, TMD monolayers which exhibit defect density, charge carrier mobility, and excitonic properties intrinsic to the parent crystal. Finally, post-process patterning and stacking are explored
Methods for Measurement and Inference in Large-scale Systems: Applications in Public Policy and Large Language Models
No full textThis thesis is about measurement and inference in large-scale systems where the quantities of interest cannot be directly observed. It consists of two distinct threads.
The first thread examines a well-established problem: estimating the causal effect of a public policy on a large population, such as the state-wide effect of a policy change. Since we cannot observe what would have happened without the intervention, we must rely on modeling assumptions. Synthetic control methods address this challenge by approximating a unit's counterfactual outcomes using a weighted combination of other units' observed outcomes.
However, this raises a fundamental question: when and why does this linear combination assumption actually hold? In chapter one, we develop a new conceptual framework and derive sufficient conditions for nonparametric identification for synthetic control methods. Chapter two extends this framework by deriving error bounds when the linear assumption fails and developing estimators that minimize these errors.
The second thread tackles a newer but equally challenging problem: understanding large language models. Unlike policy evaluation, where decades of methodological development provide established approaches, measuring what these models have learned presents entirely novel challenges.
We cannot directly observe the beliefs or capabilities encoded within these systems, yet understanding them is crucial for their deployment. This thread approaches the measurement challenge from two angles: external evaluation and internal representation.
In chapter three, we focus on external evaluation by developing methods to measure the moral beliefs that large language models express through their outputs, adapting survey methodology to work with AI systems as respondents and creating specialized evaluation metrics and datasets. Chapter four shifts to internal representation, investigating how computational capabilities are organized within these models by testing the hypothesis that specific abilities are executed by small subnetworks called "circuits" through formalized criteria and statistical hypothesis tests