Encounters beyond the interface: Data structures, material feminisms, and composition

This dissertation argues that data literacy should be taught in college writing classes along with other new media literacies. Drawing from several areas of study, this dissertation establishes a definition of data literacy, introduces a feminist methodological approach to Big Data and data studies, and makes a case for teaching data literacy in first year composition and professional writing courses as a foundational writing-related literacy. Information written into and read from databases supports research activities in any number of fields from STEM to the humanities; while different disciplines approach databases and data structures from diverse perspectives, all students need foundational data literacies. Nearly all digital environments are facilitated in some way by databases. They drive a range of web applications in ways that most users do not realize. On the surface, only GUIs are visible, and sets of data could be presented in any number of ways through them in the form of visuals, texts, and sound. It is important that students learn how data structures influence what comes across in the interface. By having students rhetorically analyze databases and then create them, composition teachers can help to demystify these ubiquitous yet invisible technocultural objects. Becoming aware of data structures gives students insight into how digital compositions emerge, empowering them to be more than “users” or “subjects” that use technological “objects.” Ideally, they would gain insight into how both “sides” of this encounter arise in dependence on many contributing factors, such as the standards, classifications, and categories perpetuated by techno-cultural infrastructures. Developing a socio-ontological methodology that combines scholarship in both feminist new materialisms and feminist rhetorical methodologies, this dissertation discusses the importance of researcher positionality. The socio-ontological methodology developed here expands on social constructivist theories to view all participants in a situation, including non-human ones, as mutually existing in dependence upon each other. Within this framework, contemplative mapping helps to articulate how the researcher does not exist outside of the research situation and assists in helping to make the situation uncanny, so that we can question assumptions and think through processes. Providing a foundational understanding of why data structures have become important to our professional and personal lives, this dissertation explains the public fascination with Big Data and exposes the ways that individuals can be affected by data collection practices, examining how the data structures that enable what comes across in user interfaces can be understood and taught in the context of writing studies

Amyloid-related memory decline in preclinical Alzheimer\u27s disease in dependent on APOE ε4 and is detectable over 18-months

High levels of β-amyloid (Aβ) in the brain and carriage of the APOE ε4 allele have each been linked to cognitive impairment in cognitively normal (CN) older adults. The aim of this study was to investigate the relationship between cerebral Aβ level, APOE ε4 carrier status, and cognitive decline over 18 monthes, in 317 cognitively healthy (CN) older adults (47% males, 52.4% females) aged between 60 and 89 years (Mean = 69.9, SC = 6.8). Cognition was assessed using the Cogstate Brief Battery (CBB) and the California Verbal Learning Test, Second Edition (CVLT-II). Planned comparisons indicated that CN older adults with high Aβ who were also APOE ε4 carriers demonstrated the most pronounced decline in learning and working memory. In CN older adults who were APOE ε4 non-carriers, high Aβwas unrelated to cognitive decline in learning and working memory. Carriage of APOE ε4 in CN older adults with low Aβ was associated with a significantly increased rate of decline in learning and unexpectedly, improved cognitive performance on measures of verbal episodic memory over 18 months. These results suggest that Aβ and APOE ε4 interact to increase the rate of cognitive decline in CN older adults and provide further support for the use of Aβ and APOE ε4 as biomarkers of early Alzheimer’s disease

Galaxy Zoo DESI: Detailed Morphology Measurements for 8.7M Galaxies in the DESI Legacy Imaging Surveys

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5-10\% for every answer to every GZ question. The models are trained on newly-collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly-collected votes. Extending our morphology measurements outside of the previously-released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5,000 to 19,000 deg$^2$) and allows for full overlap with complementary surveys including ALFALFA and MaNGA.Comment: 20 pages. Accepted at MNRAS. Catalog available via https://zenodo.org/record/7786416. Pretrained models available via https://github.com/mwalmsley/zoobot. Vizier and Astro Data Lab access not yet available. With thanks to the Galaxy Zoo volunteer

Pharmacological validation of targets regulating CD14 during macrophage differentiation

The signalling receptor for LPS, CD14, is a key marker of, and facilitator for, pro-inflammatory macrophage function. Pro-inflammatory macrophage differentiation remains a process facilitating a broad array of disease pathologies, and has recently emerged as a potential target against cytokine storm in COVID19. Here, we perform a whole-genome CRISPR screen to identify essential nodes regulating CD14 expression in myeloid cells, using the differentiation of THP-1 cells as a starting point. This strategy uncovers many known pathways required for CD14 expression and regulating macrophage differentiation while additionally providing a list of novel targets either promoting or limiting this process. To speed translation of these results, we have then taken the approach of independently validating hits from the screen using well-curated small molecules. In this manner, we identify pharmacologically tractable hits that can either increase CD14 expression on non-differentiated monocytes or prevent CD14 upregulation during macrophage differentiation. An inhibitor for one of these targets, MAP2K3, translates through to studies on primary human monocytes, where it prevents upregulation of CD14 following M-CSF induced differentiation, and pro-inflammatory cytokine production in response to LPS. Therefore, this screening cascade has rapidly identified pharmacologically tractable nodes regulating a critical disease-relevant process

Galaxy Zoo DESI : Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5–10% for every answer to every GZ question. The models are trained on newly-collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly-collected votes. Extending our morphology measurements outside of the previously-released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5000 to 19 000 deg2) and allows for full overlap with complementary surveys including ALFALFA and MaNGA

Galaxy Zoo DESI: Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5–10% for every answer to every GZ question. The models are trained on newly-collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly-collected votes. Extending our morphology measurements outside of the previously-released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5000 to 19 000 deg2) and allows for full overlap with complementary surveys including ALFALFA and MaNGA

Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer’s disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast “resilient” unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk

Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155922/1/pmic13292_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155922/2/pmic13292.pd

Fifteen years of the Australian imaging, biomarkers and lifestyle (AIBL) study: Progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer\u27s disease

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer\u27s disease dementia (AD)) as an \u27Inception cohort\u27 who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an \u27Enrichment cohort\u27 (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims