A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

National identity predicts public health support during a global pandemic (vol 13, 517, 2022) : National identity predicts public health support during a global pandemic (Nature Communications, (2022), 13, 1, (517), 10.1038/s41467-021-27668-9)

Publisher Copyright: © The Author(s) 2022.In this article the author name ‘Agustin Ibanez’ was incorrectly written as ‘Augustin Ibanez’. The original article has been corrected.Peer reviewe

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics

Author Correction: National identity predicts public health support during a global pandemic

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27668-9, published online 26 January 2022

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Engineering antibody therapeutics and cell culture models for neurodegenerative diseases

Colby, David W.Neurodegenerative diseases are typically characterized by selective neuronal subtype vulnerability and associated incorrectly processed and misfolded amyloidogenic proteins. These disease pathologies differentially affect anatomically specialized areas made up of dozens of different subtypes of neurons interconnected in complicated pathways. Currently, there are no established treatments to halt or even slow the progression of these diseases. To deconvolute these interacting effectors of neuronal dysfunction, we can develop neurodegeneration cell culture models to break up different components into intrinsic and extrinsic effects. Intrinsic effects consist of age-related dysfunction and neuron subtype identity and how the type of neuron mediates selective vulnerability. Extrinsic effects include neuro-inflammation factors, apoptotic factors released from nearby dying cells, and misfolded disease proteins such as tau protein as they travel through the brain. By understanding some of these effects in isolation we can identify points of therapeutic intervention and quantify disease biomarkers to track disease progression and therapeutic efficacy. In this work, we develop a high-throughput platform for neuronal reprogramming to culture specific subtypes of patient-derived neurons for studying cell type-specific intrinsic properties, we establish an improved culture model of tau protein disease strain fibrillization to study extrinsically-added misfolded protein, and we demonstrate the feasibility of engineering therapeutic proteins in a heterologous host for improved stability and expression. ☐ Huntington’s disease (HD) is a dominantly inherited, progressive neurodegenerative disease characterized by specific and extensive loss of medium spiny neurons during striatal degeneration. It remains unclear whether this cell-type selectivity is primarily due to intrinsic cell-autonomous effects or neuronal dysfunction in surrounding neurons. The ability to obtain relevant cell-types in vitro would be an invaluable resource to study these cell-type specific effects. We assembled and screened a library of transcription factors to reprogram human fibroblasts or induced pluripotent stem cells from HD and non-HD patients into neuronal subtypes important in HD. We also developed a combinatorial computational model to assist in the selection of experimental parameters to optimize library screening efficiency. The resulting identified sets of transcription factors may be used to develop a fast, reproducible in vitro model that accurately captures the major phenotypic characteristics of HD in order to further understand the intrinsic cell-type specific pathogenesis of the disease. ☐ The microtubule-associated protein tau stabilizes microtubules in neurons for cytoskeletal support and cellular trafficking. Fibrillization and accumulation of tau is a defining characteristic of a group of neurodegenerative diseases called “tauopathies” in which tau forms distinct fibril strain conformations across different tauopathies which may contribute to their unique histological and clinical characteristics. Most current tauopathy cell models rely on the application of synthetic tau fibrils formed by induced fibrillization with the poly-anion heparin. While it has been previously demonstrated that heparin-induced fibrils are structurally distinct from brain-derived tauopathy fibrils, we have shown that synthetic fibrils are also significantly different when propagated in a cell culture model of extrinsically-applied tau strain propagation. Additionally, while truncated or mutant tau has been useful to study the mechanics of synthetic fibril propagation, we have shown that full length wild type tau is better suited for propagation of disease-associated strains in this model. The cell culture model presented in this study may be broadly applicable to many other neurodegenerative diseases. ☐ The protein-only hypothesis for prion-like diseases asserts that neurodegenerative disease-associated proteins such as the prion protein or tau protein can spread their misfolded disease conformation to natively folded protein by direct intermolecular interaction to template the misfolded structure. Understanding this interaction suggests a therapeutic approach in which a specifically-binding therapeutic may be able to disrupt the interaction of native and misfolded protein to halt the progression of the disease. We chose an anti-prion antibody ICSM18 that was previously engineered by our group to better understand the feasibility and fidelity of engineering therapeutic proteins in a heterologous host. CHO cells are the most common platform for protein secretion in the pharmaceutical industry, but Saccharomyces cerevisiae are an attractive engineering platform because of their eukaryotic expression machinery and rapid doubling time. We found that apparent affinity by yeast display may be significantly lowered by differences in expression machinery between the two expression systems but that improvements in stability in yeast translate directly to improved expression yields in CHO cells which indicates that yeast display may not provide exact affinity estimation but that complex protein therapeutics may still be efficiently engineered in a heterologous host.University of Delaware, Department of Chemical and Biomolecular EngineeringPh.D

Improving NADPH availability for natural product biosynthesis in Escherichia coli by metabolic engineering.

a b s t r a c t With microbial production becoming the primary choice for natural product synthesis, increasing precursor and cofactor availability has become a chief hurdle for the generation of efficient production platforms. As such, we employed a stoichiometric-based model to identify combinations of gene knockouts for improving NADPH availability in Escherichia coli. Specifically, two different model objectives were used to identify possible genotypes that exhibited either improved overall NADPH production or an improved flux through an artificial reaction coupling NADPH yield to biomass. The top single, double and triple gene deletion candidates were constructed and as a case study evaluated for their ability to produce two polyphenols, leucocyanidin and (+)-catechin. Each is derived from their common precursor dihydroquercetin using two recombinant NADPH-dependent enzymes: dihydroflavonol 4-reductase and leucoanthocyanidin reductase. The best engineered strain carrying Dpgi, Dppc and DpldA deletions accumulated up to 817 mg/L of leucocyanidin and 39 mg/L (+)-catechin in batch culture with 10 g/L glucose in modified M9 medium, a 4-fold and 2-fold increase, respectively, compared to the wild-type control