Illuminating Perceptions of Social-Ecological Complexity for More Holistic Management of Parks and Protected Areas

This dissertation focuses on illuminating human perceptions in a social-ecological system (SES) through three studies: (1) revealing human perceptions of the influence of social network structure on social dynamics in an SES; (2) understanding human perceptions of biophysical and social change related to a SES, and (3) exploring how key stakeholder groups might perceive social-ecological reciprocities in an SES. To achieve these endeavors, this dissertation advances analytical tools that have yet to be widely used in natural resource management to understand stakeholders’ perceptions of social-ecological complexity: social network models, perceptions of change, and fuzzy logic cognitive mapping. These tools represent a combination of objective social analysis, inquiry into subjective perceptions, and subjective mental modeling, all of which may be useful for natural resource managers who need or desire to engage in SES thinking. The three studies herein thus apply these tools to the complex social-ecological system known as the Bonneville Salt Flats (BSF) in western Utah (USA)

Genetic analysis of pseudohyphal growth in the budding yeast Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is a dimorphic organism that can assume either a yeast-like or pseudohyphal form. Nitrogen limitation induces pseudohyphal growth, which is characterized by branched chains of elongated cells. Pseudohyphal cells can grow invasively in agar medium, whereas yeast-like cells do not. To identify factors involved in morphologic differentiation, S. cerevisiae mutants exhibiting a constitutive cell elongation morphology were isolated. Genetic analysis identified 28 recessive and 2 semi-dominant mutations that cause abnormal morphology, and placed these in 14 distinct gene loci, termed ELM, for ELongated Morphology. Many elm mutations cause multiple aspects of pseudohyphal growth, and thus are proposed to allow execution of a specific morphologic differentiation pathway in inappropriate conditions. Supporting this hypothesis, gene dosage at several ELM loci affected pseudohyphal differentiation in response to nitrogen limitation. Genetic interactions were detected between many elm mutations, suggesting these genes function in the same, or functionally related biological pathways;Molecular cloning studies identified several proteins likely to be involved in morphologic differentiation in S. cerevisiae. ELM1 was isolated and shown to code for a protein similar in amino acid sequence to known serine/threonine protein kinases. Mutations in ELM1 showed genetic interactions with a mutation in CDC55 that affects a protein similar in amino acid sequence to the B regulatory subunit of mammalian protein phosphatase 2A. Thus, protein phosphorylation is likely to be involved in pseudohyphal differentiation. ELM13 was found to be identical to CDC12, which codes for a component of the 10 nm filament structure located at the bud neck. Loss of function of PPS1, a gene coding for phosphoribosylpyrophosphate synthase, a key rate limiting enzyme in the biosynthesis of histidine, tryptophan, and purine and pyrimidine nucleotides, interacts genetically with elm4-1 to potentiate the constitutive pseudohyphal growth phenotype;These results suggest an ordered signal transduction pathway recognizes conditions of nitrogen limitation and then causes pseudohyphal differentiation to occur. Loss of function mutations in ELM genes are proposed to alter this pathway, resulting in constitutive pseudohyphal growth

Ectopic histone H3S10 phosphorylation causes chromatin structure remodeling in Drosophila

Histones are subject to numerous post-translational modifications that correlate with the state of higher-order chromatin structure and gene expression. However, it is not clear whether changes in these epigenetic marks are causative regulatory factors in chromatin structure changes or whether they play a mainly reinforcing or maintenance role. In Drosophila phosphorylation of histone H3S10 in euchromatic chromatin regions by the JIL-1 tandem kinase has been implicated in counteracting heterochromatization and gene silencing. Here we show, using a LacI-tethering system, that JIL-1 mediated ectopic histone H3S10 phosphorylation is sufficient to induce a change in higher-order chromatin structure from a condensed heterochromatin-like state to a more open euchromatic state. This effect was absent when a `kinase dead\u27 LacI-JIL-1 construct without histone H3S10 phosphorylation activity was expressed. Instead, the `kinase dead\u27 construct had a dominant-negative effect, leading to a disruption of chromatin structure that was associated with a global repression of histone H3S10 phosphorylation levels. These findings provide direct evidence that the epigenetic histone tail modification of H3S10 phosphorylation at interphase can function as a causative regulator of higher-order chromatin structure in Drosophila in vivo

Using the data quality dashboard to improve the ehden network

Federated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collaboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Fifteen Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance issues but showed less of an impact on completeness and plausibility checks. This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.</p

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data

Background and objective: As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). Methods: We show step-by-step how to implement the analytics pipeline for the question: ‘In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?’. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Results: Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion: Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.</p

A Novel Genetic Screen Implicates Elm1 in the Inactivation of the Yeast Transcription Factor SBF

BACKGROUND: Despite extensive large scale analyses of expression and protein-protein interactions (PPI) in the model organism Saccharomyces cerevisiae, over a thousand yeast genes remain uncharacterized. We have developed a novel strategy in yeast that directly combines genetics with proteomics in the same screen to assign function to proteins based on the observation of genetic perturbations of sentinel protein interactions (GePPI). As proof of principle of the GePPI screen, we applied it to identify proteins involved in the regulation of an important yeast cell cycle transcription factor, SBF that activates gene expression during G1 and S phase. METHODOLOGY/PRINCIPLE FINDINGS: The principle of GePPI is that if a protein is involved in a pathway of interest, deletion of the corresponding gene will result in perturbation of sentinel PPIs that report on the activity of the pathway. We created a fluorescent protein-fragment complementation assay (PCA) to detect the interaction between Cdc28 and Swi4, which leads to the inactivation of SBF. The PCA signal was quantified by microscopy and image analysis in deletion strains corresponding to 25 candidate genes that are periodically expressed during the cell cycle and are substrates of Cdc28. We showed that the serine-threonine kinase Elm1 plays a role in the inactivation of SBF and that phosphorylation of Elm1 by Cdc28 may be a mechanism to inactivate Elm1 upon completion of mitosis. CONCLUSIONS/SIGNIFICANCE: Our findings demonstrate that GePPI is an effective strategy to directly link proteins of known or unknown function to a specific biological pathway of interest. The ease in generating PCA assays for any protein interaction and the availability of the yeast deletion strain collection allows GePPI to be applied to any cellular network. In addition, the high degree of conservation between yeast and mammalian proteins and pathways suggest GePPI could be used to generate insight into human disease

The spindle position checkpoint is coordinated by the Elm1 kinase

Localization and activation of Elm1 at the bud neck coordinates SPC activity with mother–daughter polarity during cell division

International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients

Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale healthcare databases to generate comprehensive evidence in a transparent and reproducible manner.Methods: In this international cohort study, we deployed electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We assessed association between alpha-1 blocker use and risks of three COVID-19 outcomes-diagnosis, hospitalization, and hospitalization requiring intensive services-using a prevalent-user active-comparator design. We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We pooled database-specific estimates through random effects meta-analysis.Results: Our study overall included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH medications. We observed no significant difference in their risks for any of the COVID-19 outcomes, with our meta-analytic HR estimates being 1.02 (95% CI: 0.92-1.13) for diagnosis, 1.00 (95% CI: 0.89-1.13) for hospitalization, and 1.15 (95% CI: 0.71-1.88) for hospitalization requiring intensive services.Conclusion: We found no evidence of the hypothesized reduction in risks of the COVID-19 outcomes from the prevalent-use of alpha-1 blockers-further research is needed to identify effective therapies for this novel disease.</p

Phenotype Algorithms for the Identification and Characterization of Vaccine-Induced Thrombotic Thrombocytopenia in Real World Data: A Multinational Network Cohort Study

INTRODUCTION: Vaccine-induced thrombotic thrombocytopenia (VITT) has been identified as a rare but serious adverse event associated with coronavirus disease 2019 (COVID-19) vaccines. OBJECTIVES: In this study, we explored the pre-pandemic co-occurrence of thrombosis with thrombocytopenia (TWT) using 17 observational health data sources across the world. We applied multiple TWT definitions, estimated the background rate of TWT, characterized TWT patients, and explored the makeup of thrombosis types among TWT patients. METHODS: We conducted an international network retrospective cohort study using electronic health records and insurance claims data, estimating background rates of TWT amongst persons observed from 2017 to 2019. Following the principles of existing VITT clinical definitions, TWT was defined as patients with a diagnosis of embolic or thrombotic arterial or venous events and a diagnosis or measurement of thrombocytopenia within 7 days. Six TWT phenotypes were considered, which varied in the approach taken in defining thrombosis and thrombocytopenia in real world data. RESULTS: Overall TWT incidence rates ranged from 1.62 to 150.65 per 100,000 person-years. Substantial heterogeneity exists across data sources and by age, sex, and alternative TWT phenotypes. TWT patients were likely to be men of older age with various comorbidities. Among the thrombosis types, arterial thrombotic events were the most common. CONCLUSION: Our findings suggest that identifying VITT in observational data presents a substantial challenge, as implementing VITT case definitions based on the co-occurrence of TWT results in large and heterogeneous incidence rate and in a cohort of patints with baseline characteristics that are inconsistent with the VITT cases reported to date

Phenotype Algorithms for the Identification and Characterization of Vaccine-Induced Thrombotic Thrombocytopenia in Real World Data:A Multinational Network Cohort Study

INTRODUCTION: Vaccine-induced thrombotic thrombocytopenia (VITT) has been identified as a rare but serious adverse event associated with coronavirus disease 2019 (COVID-19) vaccines. OBJECTIVES: In this study, we explored the pre-pandemic co-occurrence of thrombosis with thrombocytopenia (TWT) using 17 observational health data sources across the world. We applied multiple TWT definitions, estimated the background rate of TWT, characterized TWT patients, and explored the makeup of thrombosis types among TWT patients. METHODS: We conducted an international network retrospective cohort study using electronic health records and insurance claims data, estimating background rates of TWT amongst persons observed from 2017 to 2019. Following the principles of existing VITT clinical definitions, TWT was defined as patients with a diagnosis of embolic or thrombotic arterial or venous events and a diagnosis or measurement of thrombocytopenia within 7 days. Six TWT phenotypes were considered, which varied in the approach taken in defining thrombosis and thrombocytopenia in real world data. RESULTS: Overall TWT incidence rates ranged from 1.62 to 150.65 per 100,000 person-years. Substantial heterogeneity exists across data sources and by age, sex, and alternative TWT phenotypes. TWT patients were likely to be men of older age with various comorbidities. Among the thrombosis types, arterial thrombotic events were the most common. CONCLUSION: Our findings suggest that identifying VITT in observational data presents a substantial challenge, as implementing VITT case definitions based on the co-occurrence of TWT results in large and heterogeneous incidence rate and in a cohort of patints with baseline characteristics that are inconsistent with the VITT cases reported to date. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40264-022-01187-y