3,268 research outputs found

    A Political Theory of Engineered Systems and A Study of Engineering and Justice Workshops

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    Since there are good reasons to think that some engineered systems are socially undesirable—for example, internal combustion engines that cause climate change, algorithms that are racist, and nuclear weapons that can destroy all life—there is a well-established literature that attempts to identify best practices for designing and regulating engineered systems in order to prevent harm and promote justice. Most of this literature, especially the design theory and engineering justice literature meant to help guide engineers, focuses on environmental, physical, social, and mental harms such as ecosystem and bodily poisoning, racial and gender discrimination, and urban alienation. However, the literature that focuses on how engineered systems can produce political harms—harms to how we shape the way we live in community together—is not well established. The first part of this thesis contributes to identifying how particular types of engineered systems can harm a democratic politics. Building on democratic theory, philosophy of collective harms, and design theory, it argues that engineered systems that extend in space and time beyond a certain threshold subvert the knowledge and empowerment necessary for a democratic politics. For example, the systems of global shipping and the internet that fundamentally shape our lives are so large that people cannot attain the knowledge necessary to regulate them well nor the empowerment necessary to shape them. The second part of this thesis is an empirical study of a workshop designed to encourage engineering undergraduates to understand how engineered systems can subvert a democratic politics, with the ultimate goal of supporting students in incorporating that understanding into their work. 32 Dartmouth undergraduate engineering students participated in the study. Half were assigned to participate in a workshop group, half to a control group. The workshop group participants took a pretest; then participated in a 3-hour, semi-structured workshop with 4 participants per session (as well as a discussion leader and note-taker) over lunch or dinner; and then took a posttest. The control group participants took the same pre- and post- tests, but had no suggested activity in the intervening 3 hours. We find that the students who participated in workshops had a statistically significant test-score improvement as compared to the control group (Brunner-Munzel test, p \u3c .001). Using thematic analysis methods, we show the data is consistent with the hypothesis that workshops produced a score improvement because of certain structure (small size, long duration, discussion-based, over homemade food) and content (theoretically rich, challenging). Thematic analysis also reveals workshop failures and areas for improvement (too much content for the duration, not well enough organized). The thesis concludes with a discussion of limitations and suggestions for future theoretical, empirical, and pedagogical research

    Addressing climate change with behavioral science : A global intervention tournament in 63 countries

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    Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

    Simultaneous Multiparametric and Multidimensional Cardiovascular Magnetic Resonance Imaging

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    Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial

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    On top of machine learning models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability improvement of ML models empowered by UQ has the potential to significantly facilitate the broad adoption of ML solutions in high-stakes decision settings, such as healthcare, manufacturing, and aviation, to name a few. In this tutorial, we aim to provide a holistic lens on emerging UQ methods for ML models with a particular focus on neural networks and the applications of these UQ methods in tackling engineering design as well as prognostics and health management problems. Toward this goal, we start with a comprehensive classification of uncertainty types, sources, and causes pertaining to UQ of ML models. Next, we provide a tutorial-style description of several state-of-the-art UQ methods: Gaussian process regression, Bayesian neural network, neural network ensemble, and deterministic UQ methods focusing on spectral-normalized neural Gaussian process. Established upon the mathematical formulations, we subsequently examine the soundness of these UQ methods quantitatively and qualitatively (by a toy regression example) to examine their strengths and shortcomings from different dimensions. Then, we review quantitative metrics commonly used to assess the quality of predictive uncertainty in classification and regression problems. Afterward, we discuss the increasingly important role of UQ of ML models in solving challenging problems in engineering design and health prognostics. Two case studies with source codes available on GitHub are used to demonstrate these UQ methods and compare their performance in the life prediction of lithium-ion batteries at the early stage and the remaining useful life prediction of turbofan engines

    Computational Approaches to Drug Profiling and Drug-Protein Interactions

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    Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster

    Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin

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    Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum

    Rational development of stabilized cyclic disulfide redox probes and bioreductive prodrugs to target dithiol oxidoreductases

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    Countless biological processes allow cells to develop, survive, and proliferate. Among these, tightly balanced regulatory enzymatic pathways that can respond rapidly to external impacts maintain dynamic physiological homeostasis. More specifically, redox homeostasis broadly affects cellular metabolism and proliferation, with major contributions by thiol/disulfide oxidoreductase systems, in particular, the Thioredoxin Reductase Thioredoxin (TrxR/Trx) and the Glutathione Reductase-Glutathione-Glutaredoxin (GR/GSH/Grx) systems. These cascades drive vital cellular functions in many ways through signaling, regulating other proteins' activity by redox switches, and by stoichiometric reductant transfers in metabolism and antioxidant systems. Increasing evidence argues that there is a persistent alteration of the redox environment in certain pathological states, such as cancer, that heavily involve the Trx system: upregulation and/or overactivity of the Trx system may support or drive cancer progression, making both TrxR and Trx promising targets for anti-cancer drug development. Understanding the biochemical mechanisms and connections between certain redox cascades requires research tools that interact with them. The state-of-the-art genetic tools are mostly ratiometric reporters that measure reduced:oxidized ratios of selected redox pairs or the general thiol pool. However, the precise cellular roles of the central oxidoreductase systems, including TrxR and Trx, remain inaccessible due to the lack of probes to selectively measure turnover by either of these proteins. However, such probes would allow measuring their effective reductive activity apart from expression levels in native systems, including in cells, animals, or patient samples. They are also of high interest to identify chemical inhibitors for TrxR/Trx in cells and to validate their potential use as anti-cancer agents (to date, there is no selective cellular Trx inhibitor, and most known TrxR inhibitors were not comprehensively evaluated considering selectivity and potential off-targets). However, small molecule redox imaging tools are underdeveloped: their protein specificity, spectral properties, and applicability remain poorly precedented. This work aimed to address this opportunity gap and develop novel, small molecule diagnostic and therapeutic tools to selectively target the Trx system based on a modular trigger cargo design: artificial cyclic disulfide substrates (trigger) for oxidoreductases are tethered to molecular agents (cargo) such that the cargo’s activity is masked and is re-established only through reduction by a target protein. The rational design of these novel reduction sensors to target the cell's strongest disulfide-reducing enzymes was driven by the following principles: (i) cyclic disulfide triggers with stabilized ring systems were used to gain low reduction potentials that should resist reduction except by the strongest cellular reductases, such as Trx; and (ii) the cyclic topology also offers the potential for kinetic reversibility that should select for dithiol-type redox proteins over the cellular monothiol background. Creating imaging agents based on such two-component designs to selectively measure redox protein activity in native cells required to combine the correct trigger reducibility, probe activation kinetics, and imaging modalities and to consider the overall molecular architecture. The major prior art in this field has applied cyclic 5-membered disulfides (1,2 dithiolanes) as substrates for TrxR in a similar way to create such tools. However, this motif was described elsewhere as thermodynamically instable and was due to widely used for dynamic covalent cascade reactions. By comparing a novel 1,2 dithiolane-based probe to the state-of-the-art probes, including commercial TrxR sensors, by screening a conclusive assay panel of cellular TrxR modulations, I clarified that 1,2 dithiolanes are not selective substrates for TrxR in biological settings (Nat Commun 2022). Instead, aiming for more stable ring systems and thus more robust redox probes, during this work, I developed bicyclic 6 membered disulfides (piperidine fused 1,2 dithianes) with remarkably low reduction potentials. I showed that molecular probes using them as reduction sensors can be mostly processed by thioredoxins while being stable against reduction by GSH. The thermodynamically stabilized decalin like topology of the cis-annelated 1,2 dithianes requires particularly strong reductants to be cleaved. They also select for dithiol type redox proteins, like Trx, based on kinetic reversibility and offer fast cyclization due to the preorganization by annelation (JACS 2021). This work further expanded the system’s modularity with structural cores based on piperazine-fused 1,2 dithianes with the two amines allowing independent derivatization. Diagnostic tools using them as reduction sensors proved equally robust but with highly improved activation kinetics and were thus cellularly activated. Cellular studies evolved that they are substrates for both Trxs and their protein cousins Grxs, so measuring the cellular dithiol protein pool rather than solely Trx activity (preprint 2023). Finally, a trigger based on a slightly adapted reduction sensor, a desymmetrized 1,2 thiaselenane, was designed for selective reduction by TrxR’s selenol/thiol active site, then combined with a precipitating large Stokes’ shift fluorophore and a solubilizing group, to evolve the first selective probe RX1 to measure cellular TrxR activity, which even allowed high throughput inhibitor screening (Chem 2022). The central principle of this work was further advanced to therapeutic prodrugs based on the duocarmycin cargo (CBI) with tunable potency (JACS Au 2022) that can be used to create off-to-on therapeutic prodrugs. Such CBI prodrugs employing stabilized 1,2 dichalcogenide triggers proved to be cytotoxins that depend on Trx system activity in cells. They could further be exploited for cell-line dependent reductase activity profiling by screening their redox activation indices, the reduction-dependent part of total prodrug activation, in 177 cell lines. Beyond that, these prodrugs were well-tolerated in animals and showed anti-cancer efficacy in vivo in two distinct mouse tumor models (preprint 2022). Taken together, I introduced unique monothiol-resistant reducible motifs to target the cellular Trx system with chemocompatible units for each for TrxR and Trx/Grx, where the cyclic nature of the dichalcogenides avoids activation by GSH. By using them with distinct molecular cargos, I developed novel selective fluorescent reporter probes; and introduced a new class of bioreductive therapeutic constructs based on a common modular design. These were either applied to selectively measure cellular reductase activity or to deliver cytotoxic anti cancer agents in vivo. Ongoing work aims to differentiate between the two major redox effector proteins Trx and Grx, requiring additional layers of selectivity that may be addressed by tuned molecular recognition. The flexible use of various molecular cargos allows harnessing the same cellular redox machinery by either probes or prodrugs. This allows predictive conclusions from diagnostics to be directly translated into therapy and offers great potential for future adaptation to other enzyme classes and therapeutic venues.Die zellulĂ€re Redox-Homöostase hĂ€ngt von Thiol/Disulfid-Oxidoreduktasen ab, die den Stoffwechsel, die Proliferation und die antioxidative Antwort von Zellen beeinflussen. Die wichtigsten Netzwerke sind die Thioredoxin Reduktase-Thioredoxin (TrxR/Trx) und Glutathion Reduktase-Glutathion-Glutaredoxin (GR/GSH/Grx) Systeme, die ĂŒber Redox-Schalter in Substratproteinen lebenswichtige zellulĂ€re Funktionen steuern und so an der Redox-Regulation und -SignalĂŒbertragung beteiligt sind. Persistente VerĂ€nderungen des Redoxmilieus in pathologischen ZustĂ€nden, wie z. B. bei Krebs, sind in hohem Maße mit dem Trx-System verbunden. Eine Hochregulierung und/oder ÜberaktivitĂ€t des Trx-Systems, die bei vielen Krebsarten auftreten, unterstĂŒtzt zudem das Fortschreiten des Krebswachstums, was TrxR/Trx zu vielversprechenden Zielproteinen fĂŒr die Entwicklung neuer Krebsmedikamente macht. Um die biochemischen Prozesse dahinter zu erforschen, sind spezielle Techniken zur Visualisierung und Messung enzymatischer AktivitĂ€t nötig. Die hierzu geeigneten, meist genetischen Sensoren messen ratiometrisch das VerhĂ€ltnis reduzierter/oxidierter Spezies in zellulĂ€rem Umfeld oder spezifisch ausgewĂ€hlte Redoxpaare. Die weitere Erforschung der exakten Funktion von TrxR/Trx und deren Substrate ist jedoch durch mangelnde Nachweismethoden limitiert. Diese sind außerdem zur Validierung chemischer Hemmstoffe fĂŒr TrxR/Trx in Zellen und deren potenziellen Verwendung als Krebsmittel von großem Interesse. Bislang gibt es keinen selektiven zellulĂ€ren Trx-Inhibitor und potenzielle Off-Target-Effekte der bekannten TrxR-Inhibitoren wurden nicht abschließend bewertet. Ziel dieser Arbeit ist die Entwicklung niedermolekularer, diagnostischer und therapeutischer Werkzeuge, die selektiv auf das Trx-System abzielen und auf einem modularen Trigger-Cargo Design basieren. Hierzu werden zyklische Disulfid-Substrate (Trigger) fĂŒr Oxidoreduktasen so mit molekularen Wirkstoffen (Cargo) verknĂŒpft, dass dabei die WirkstoffaktivitĂ€t maskiert, und erst nach Reduktion durch ein Zielprotein wiederhergestellt wird. Diese neuartigen, synthetischen Reduktionssensoren basieren auf den folgenden Grundprinzipien: (i) Zyklische Disulfide sind thermodynamisch stabilisiert und können nur durch die stĂ€rksten Reduktasen gespalten werden; und (ii) die zyklische Topologie ermöglicht die kinetische ReversibilitĂ€t der zwei Thiol-Disulfid-Austauschreaktionen, die eine erste Reaktion mit Monothiolen, wie z. B. GSH, sofort umkehrt und so eine vollstĂ€ndige Reduktion verhindert. Die meisten frĂŒheren Arbeiten auf diesem Gebiet verwendeten ein zyklisches, fĂŒnfgliedriges Disulfid (1,2 Dithiolan) als Substrat fĂŒr TrxR. Das gleiche Strukturmotiv wurde jedoch an anderer Stelle als thermodynamisch instabil beschrieben und aufgrund dieser Eigenschaft explizit fĂŒr dynamische Kaskadenreaktionen verwendet. Deshalb vergleicht diese Arbeit zu Beginn einen neuen 1,2 Dithiolan basierten fluorogenen Indikator mit bestehenden, z. T. kommerziellen, Redox Sonden fĂŒr TrxR in einer Reihe von Zellkultur-Experimenten unter Modulation der zellulĂ€ren TrxR AktivitĂ€t und stellt so einen Widerspruch in der Literatur klar: 1,2 Dithiolane eignen sich nicht als selektive Substrate fĂŒr TrxR, da sie labil sowohl gegen die Reduktion durch andere Redoxproteine, als auch gegen den Monothiol Hintergrund in Zellen sind (Nat. Commun. 2022). Als alternatives Strukturmotiv wird in dieser Arbeit ein bizyklisches sechsgliedriges Disulfid (anneliertes 1,2 Dithian) etabliert. Durch sein niedriges Reduktionspotenzial, also seine hohe Resistenz gegen Reduktion, werden molekulare Sonden basierend auf diesem 1,2 Dithian als Reduktionssensor fast ausschließlich von Trx aktiviert, nicht aber von TrxR oder GSH (JACS 2021). Dieses Kernmotiv bestimmt dabei die Reduzierbarkeit, und damit die EnzymspezifitĂ€t, durch seine zyklische Natur und die Annelierung, auch unter Verwendung unterschiedlicher Farb-/Wirkstoffe. Auf dieser Grundlage konnte die molekulare Struktur durch einen weiteren Modifikationspunkt fĂŒr die flexible Verwendung weiterer funktioneller Einheiten ergĂ€nzt werden. Obwohl zellulĂ€re Studien ergaben, dass diese neuartigen 1,2 Dithian Einheiten in Zellen sowohl Trx als auch das strukturell verwandte Grx adressieren, sind die daraus resultierenden diagnostischen MolekĂŒle wertvoll, um den katalytischen Umsatz zellulĂ€rer Dithiol-Reduktasen, der sogenannten Trx Superfamilie, selektiv anzuzeigen (Preprint 2023). BegĂŒnstigt durch das modulare MolekĂŒldesign stellt diese Arbeit zudem das erste Reportersystem RX1 zum selektiven Nachweis der TrxR-AktivitĂ€t in Zellen vor. Es basiert auf der Verwendung eines zyklischen, unsymmetrischen Selenenylsulfid-Sensors (1,2 Thiaselenan), der selektiv von dem einzigartigen Selenolat der TrxR angegriffen wird, und dadurch letztlich nur von TrxR reduziert werden kann. RX1 eignete sich zudem fĂŒr eine Hochdurchsatz-Validierung bestehender TrxR Inhibitoren und unterstreicht dadurch den kommerziellen Nutzen derartiger Diagnostika (Chem 2022). Das zentrale Trigger-Cargo Konzept dieser Arbeit wurde fĂŒr therapeutische Zwecke weiterentwickelt und nutzt dabei den einzigartigen Wirkmechanismus der Duocarmycin-Naturstoffklasse (CBI) (JACS Au 2022) zur Entwicklung reduktiv aktivierbarer Therapeutika. CBI Prodrugs basierend auf stabilisierten Redox-Schaltern (1,2 Dithiane fĂŒr Trx; 1,2 Thiaselenan fĂŒr TrxR) reagierten signifikant auf TrxR-Modulation in Zellen. Sie wurden darĂŒber hinaus durch das Referenzieren ihrer AktivitĂ€t gegenĂŒber nicht-reduzierbaren KontrollmolekĂŒle fĂŒr die Erstellung zelllinienabhĂ€ngiger Profile der ReduktaseaktivitĂ€t in 177 Zelllinien genutzt. Schließlich waren diese neuen Krebsmittel im Tiermodell gut vertrĂ€glich und zeigten in zwei verschiedenen Mausmodellen eine krebshemmende Wirkung (Preprint 2022b). Zusammenfassend prĂ€sentiert diese Dissertation monothiol-resistente reduzierbare Trigger-Einheiten fĂŒr das zellulĂ€re Trx-System zur Entwicklung neuartiger, selektiver Reporter-Sonden, sowie eine neue Klasse reduktiv aktivierbarer Krebsmittel auf Basis eines adaptierbaren Trigger-Cargo Designs. Diese fanden entweder zur selektiven Messung zellulĂ€rer ProteinaktivitĂ€t oder zum Einsatz als Antikrebsmittel Verwendung. Es wurden chemokompatible Motive sowohl fĂŒr TrxR als auch fĂŒr Trx/Grx identifiziert, wobei deren zyklische Natur eine Aktivierung durch GSH verhindert. Eine weitere Differenzierung zwischen den beiden Redox-Proteinen Trx und Grx und anderen Proteinen der Trx-Superfamilie erfordert eine zusĂ€tzliche Ebene der Selektierung, z. B. durch molekulare Erkennung, und ist Gegenstand laufender Arbeiten. Die flexible Verwendung verschiedener molekularer Wirkstoffe ermöglicht dabei die „Pipeline-Entwicklung“ von Diagnostika und Therapeutika, die von der zellulĂ€ren Redox-Maschinerie analog umgesetzt werden, und dadurch Schlussfolgerungen aus der Diagnostik direkt auf eine Therapie ĂŒbertragbar machen. Dies birgt großes Potenzial fĂŒr kĂŒnftige Entwicklungen bei einer potenziellen Übertragung des modularen Konzepts auf andere Enzymklassen und therapeutische Einsatzgebiete

    Investigating tricky nodes in the Tree of Life

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