Human iPSC-Based Model of COPD to Investigate Disease Mechanisms, Predict SARS-COV-2 Outcome, and Test Preventive Immunotherapy.

Chronic inflammation and dysregulated repair mechanisms after epithelial damage have been implicated in chronic obstructive pulmonary disease (COPD). However, the lack of ex vivo-models that accurately reflect multicellular lung tissue hinders our understanding of epithelial-mesenchymal interactions in COPD. Through a combination of transcriptomic and proteomic approaches applied to a sophisticated in vitro iPSC-alveolosphere with fibroblasts model, epithelial-mesenchymal crosstalk was explored in COPD and following SARS-CoV-2 infection. These experiments profiled dynamic changes at single-cell level of the SARS-CoV-2-infected alveolar niche that unveiled the complexity of aberrant inflammatory responses, mitochondrial dysfunction, and cell death in COPD, which provides deeper insights into the accentuated tissue damage/inflammation/remodeling observed in patients with SARS-CoV-2 infection. Importantly, this 3D system allowed for the evaluation of ACE2-neutralizing antibodies and confirmed the potency of this therapy to prevent SARS-CoV-2 infection in the alveolar niche. Thus, iPSC-alveolosphere cultured with fibroblasts provides a promising model to investigate disease-specific mechanisms and to develop novel therapeutics.

Rational design of chimeric antigen receptor T cells against glypican 3 decouples toxicity from therapeutic efficacy.

BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy has yielded impressive clinical results in hematological malignancies and is a promising approach for solid tumor treatment. However, toxicity, including cytokine-release syndrome (CRS) and neurotoxicity, is a concern hampering its broader use. METHODS: In selecting a lead CAR-T candidate against the oncofetal antigen glypican 3 (GPC3), we compared CARs bearing a low- and high-affinity single-chain variable fragment (scFv) binding to a similar epitope and cross-reactive with murine GPC3. RESULTS: Where the high-affinity CAR-T cells were toxic in vivo, the low-affinity CAR maintained cytotoxic function against antigen-positive tumor cells but did not show toxicity against normal tissues. High-affinity CAR-induced toxicity was caused by on-target, off-tumor binding, based on the observation that higher doses of the high-affinity CAR-T caused toxicity in non-tumor-bearing mice and accumulated in organs with low expression of GPC3. To explore another layer of controlling CAR-T toxicity, we developed a means to target and eliminate CAR-T cells using anti-TNF-α antibody therapy after CAR-T infusion. The antibody was shown to function by eliminating early antigen-activated, but not all, CAR-T cells, allowing a margin where the toxic response could be effectively decoupled from antitumor efficacy with only a minor loss in tumor control. By exploring additional traits of the CAR-T cells after activation, we identified a mechanism whereby we could use approved therapeutics and apply them as an exogenous kill switch that eliminated early activated CAR-T following antigen engagement in vivo. CONCLUSIONS: By combining the reduced-affinity CAR with this exogenous control mechanism, we provide evidence that we can modulate and control CAR-mediated toxicity.

Dissecting Cardiac Surgery: A Video-based Recall Protocol to Elucidate Team Cognitive Processes in the Operating Room.

OBJECTIVE: The aim of this study was to elucidate the cognitive processes involved in surgical procedures from the perspective of different team roles (surgeon, anesthesiologist, and perfusionist) and provide a comprehensive compilation of intraoperative cognitive processes. SUMMARY BACKGROUND DATA: Nontechnical skills play a crucial role in surgical team performance and understanding the cognitive processes underlying the intraoperative phase of surgery is essential to improve patient safety in the operating room (OR). METHODS: A mixed-methods approach encompassing semistructured interviews with 9 subject-matter experts. A cognitive task analysis was built upon a hierarchical segmentation of coronary artery bypass grafting procedures and a cued-recall protocol using video vignettes was used. RESULTS: A total of 137 unique surgical cognitive processes were identified, including 33 decision points, 23 critical communications, 43 pitfalls, and 38 strategies. Self-report cognitive workload varied substantially, depending on team role and surgical step. A web-based dashboard was developed, providing an integrated visualization of team cognitive processes in the OR that allows readers to intuitively interact with the study findings. CONCLUSIONS: This study advances the current body of knowledge by making explicit relevant cognitive processes involved during the intraoperative phase of cardiac surgery from the perspective of multiple OR team members. By displaying the research findings in an interactive dashboard, we provide trainees with new knowledge in an innovative fashion that could be used to enhance learning outcomes. In addition, the approach used in the present study can be used to deeply understand the cognitive factors underlying surgical adverse events and errors in the OR.

Development of a Parallel Reaction Monitoring Mass Spectrometry Assay for the Detection of SARS-CoV-2 Spike Glycoprotein and Nucleoprotein.

There is an urgent need for robust and high-throughput methods for SARS-CoV-2 detection in suspected patient samples to facilitate disease management, surveillance, and control. Although nucleic acid detection methods such as reverse transcription polymerase chain reaction (RT-PCR) are the gold standard, during the current pandemic, the deployment of RT-PCR tests has been extremely slow, and key reagents such as PCR primers and RNA extraction kits are at critical shortages. Rapid point-of-care viral antigen detection methods have been previously employed for the diagnosis of respiratory viruses such as influenza and respiratory syncytial viruses. Therefore, the direct detection of SARS-CoV-2 viral antigens in patient samples could also be used for diagnosis of active infection, and alternative methodologies for specific and sensitive viral protein detection should be explored. Targeted mass spectrometry techniques have enabled the identification and quantitation of a defined subset of proteins/peptides at single amino acid resolution with attomole level sensitivity and high reproducibility. Herein, we report a targeted mass spectrometry assay for the detection of SARS-CoV-2 spike protein and nucleoprotein in a relevant biological matrix. Recombinant full-length spike protein and nucleoprotein were digested and proteotypic peptides were selected for parallel reaction monitoring (PRM) quantitation using a high-resolution Orbitrap instrument. A spectral library, which contained seven proteotypic peptides (four from spike protein and three from nucleoprotein) and the top three to four transitions, was generated and evaluated. From the original spectral library, we selected two best performing peptides for the final PRM assay. The assay was evaluated using mock test samples containing inactivated SARS-CoV-2 virions, added to in vitro derived mucus. The PRM assay provided a limit of detection of ∼200 attomoles and a limit of quantitation of ∼ 390 attomoles. Extrapolating from the test samples, the projected titer of virus particles necessary for the detection of SARS-CoV-2 spike and nucleoprotein detection was approximately 2 × 105 viral particles/mL, making it an attractive alternative to RT-PCR assays. Potentially, mass spectrometry-based methods for viral antigen detection may deliver higher throughput and could serve as a complementary diagnostic tool to RT-PCR. Furthermore, this assay could be used to evaluate the presence of SARS-CoV-2 in archived or recently collected biological fluids, in vitro-derived research materials, and wastewater samples.

Structural insights into the mechanism of action of a biparatopic anti-HER2 antibody.

Pathways of human epidermal growth factor (EGF) receptors are activated upon ligand-dependent or -independent homo- or heterodimerization and their subsequent transphosphorylation. Overexpression of these receptors positively correlates with transphosphorylation rates and increased tumor growth rates. MEDI4276, an anti-human epidermal growth factor receptor 2 (HER2) biparatopic antibody-drug conjugate, has two paratopes within each antibody arm. One, 39S, is aiming at the HER2 site involved in receptor dimerization and the second, single chain fragment (scFv), mimicking trastuzumab. Here we present the cocrystal structure of the 39S Fab-HER2 complex and, along with biophysical and functional assays, determine the corresponding epitope of MEDI4276 and its underlying mechanism of action. Our results reveal that MEDI4276's uniqueness is based first on the ability of its 39S paratope to block HER2 homo- or heterodimerization and second on its ability to cluster the receptors on the surface of receptor-overexpressing cells.

Using process elicitation and validation to understand and improve chemotherapy ordering and delivery.

BACKGROUND: Chemotherapy ordering and administration, in which errors have potentially severe consequences, was quantitatively and qualitatively evaluated by employing process formalism (or formal process definition), a technique derived from software engineering, to elicit and rigorously describe the process, after which validation techniques were applied to confirm the accuracy of the described process. METHODS: The chemotherapy ordering and administration process, including exceptional situations and individuals' recognition of and responses to those situations, was elicited through informal, unstructured interviews with members of an interdisciplinary team. The process description (or process definition), written in a notation developed for software quality assessment purposes, guided process validation (which consisted of direct observations and semistructured interviews to confirm the elicited details for the treatment plan portion of the process). RESULTS: The overall process definition yielded 467 steps; 207 steps (44%) were dedicated to handling 59 exceptional situations. Validation yielded 82 unique process events (35 new expected but not yet described steps, 16 new exceptional situations, and 31 new steps in response to exceptional situations). Process participants actively altered the process as ambiguities and conflicts were discovered by the elicitation and validation components of the study. Chemotherapy error rates declined significantly during and after the project, which was conducted from October 2007 through August 2008. DISCUSSION: Each elicitation method and the subsequent validation discussions contributed uniquely to understanding the chemotherapy treatment plan review process, supporting rapid adoption of changes, improved communication regarding the process, and ensuing error reduction.

A Coding Framework for Usability Evaluation of Digital Health Technologies.

Several studies have reported low adherence and high resistance from clinicians to adopt digital health technologies into clinical practice, particularly the use of computer-based clinical decision support systems. Poor usability and lack of integration with the clinical workflow have been identified as primary issues. Few guidelines exist on how to analyze the collected data associated with the usability of digital health technologies. In this study, we aimed to develop a coding framework for the systematic evaluation of users' feedback generated during focus groups and interview sessions with clinicians, underpinned by fundamental usability principles and design components. This codebook also included a coding category to capture the user's clinical role associated with each specific piece of feedback, providing a better understanding of role-specific challenges and perspectives, as well as the level of shared understanding across the multiple clinical roles. Furthermore, a voting system was created to quantitatively inform modifications of the digital system based on usability data. As a use case, we applied this method to an electronic cognitive aid designed to improve coordination and communication in the cardiac operating room, showing that this framework is feasible and useful not only to better understand suboptimal usability aspects, but also to recommend relevant modifications in the design and development of the system from different perspectives, including clinical, technical, and usability teams. The framework described herein may be applied in other highly complex clinical settings, in which digital health systems may play an important role in improving patient care and enhancing patient safety.

Digital Cognitive Aids to Support Adaptation of Surgical Processes to COVID-19 Protective Policies.

Surgical processes are rapidly being adapted to address the COVID-19 pandemic, with changes in procedures and responsibilities being made to protect both patients and medical teams. These process changes put new cognitive demands on the medical team and increase the likelihood of miscommunication, lapses in judgment, and medical errors. We describe two process model driven cognitive aids, referred to as the Narrative View and the Smart Checklist View, generated automatically from models of the processes. The immediate perceived utility of these cognitive aids is to support medical simulations, particularly when frequent adaptations are needed to quickly respond to changing operating room guidelines.

Process-Model-Driven Guidance to Reduce Surgical Procedure Errors: An Expert Opinion.

This paper explains how a detailed, precise surgical process model can help reduce errors by fostering better understanding, providing guidance during surgery, helping train newcomers, and by supporting process improvement. It describes the features that a process-modeling language should have in order to support the precise specification of such models.

Process Driven Guidance for Complex Surgical Procedures.

Surgical team processes are known to be complex and error prone. This paper describes an approach that uses a detailed, validated model of a medical process to provide the clinicians who carry out that complex process with offline and online guidance to help reduce errors. Offline guidance is in the form of a hypertext document describing all the ways the process can be carried out. Online guidance is in the form of a context-sensitive and continually updated electronic "checklist" that lists next steps and needed resources, as well as completed steps. In earlier work, we focused on providing such guidance for single-clinician or single-team processes. This paper describes guiding the collaboration of multiple teams of clinicians through complex processes with significant concurrency, complicated exception handling, and precise and timely communication. We illustrate this approach by applying it to a highly complex, high risk subprocess of cardiac surgery.

Evidence for a direct link between PAD4-mediated citrullination and the oxidative burst in human neutrophils.

Neutrophils are critical for the defense against pathogens, in part through the extrusion of extracellular DNA traps, phagocytosis, and the production of reactive oxygen species. Neutrophils may also play an important role in the pathogenesis of rheumatoid arthritis (RA) through the activation of protein arginine deiminases (PADs) that citrullinate proteins that subsequently act as autoantigens. We report that PAD4 is physically associated with the cytosolic subunits of the oxidative burst machinery, p47phox (also known as neutrophil cytosol factor 1, NCF1) and p67phox (NCF2). Activation of PAD4 by membranolytic insults that result in high levels of intracellular calcium (higher than physiological neutrophil activation) leads to rapid citrullination of p47phox/NCF1 and p67phox/NCF2, as well as their dissociation from PAD4. This dissociation prevents the assembly of an active NADPH oxidase complex and an oxidative burst in neutrophils stimulated by phorbol-ester or immune complexes. In further support of a substrate-to-inactive enzyme interaction, small-molecule PAD inhibitors also disrupt the PAD4-NCF complex and reduce oxidase activation and phagocytic killing of Staphylococcus aureus. This novel role of PAD4 in the regulation of neutrophil physiology suggests that targeting PAD4 with active site inhibitors for the treatment of RA may have a broader impact on neutrophil biology than just inhibition of citrullination.

Toward Improving Surgical Outcomes by Incorporating Cognitive Load Measurement into Process-Driven Guidance.

This paper summarizes the accomplishments and recent directions of our medical safety project. Our process-based approach uses a detailed, rigorously-defined, and carefully validated process model to provide a dynamically updated, context-aware and thus, "Smart" Checklist to help process performers understand and manage their pending tasks [7]. This paper focuses on support for teams of performers, working independently as well as in close collaboration, in stressful situations that are life critical. Our recent work has three main thrusts: provide effective real-time guidance for closely collaborating teams; develop and evaluate techniques for measuring cognitive load based on biometric observations and human surveys; and, using these measurements plus analysis and discrete event process simulation, predict cognitive load throughout the process model and propose process modifications to help performers better manage high cognitive load situations. This project is a collaboration among software engineers, surgical team members, human factors researchers, and medical equipment instrumentation experts. Experimental prototype capabilities are being built and evaluated based upon process models of two cardiovascular surgery processes, Aortic Valve Replacement (AVR) and Coronary Artery Bypass Grafting (CABG). In this paper we describe our approach for each of the three research thrusts by illustrating our work for heparinization, a common subprocess of both AVR and CABG. Heparinization is a high-risk error-prone procedure that involves complex team interactions and thus highlights the importance of this work for improving patient outcomes.

Development of an Interactive Dashboard to Analyze Cognitive Workload of Surgical Teams During Complex Procedural Care.

In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member's cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member's cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. We used heart rate variability analysis, capturing data simultaneously from multiple team members (surgeon, anesthesiologist and perfusionist) in a real-time and unobtrusive manner. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the analysis of the cognitive load imposed by specific steps, substeps and/or tasks. The described approach enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies, teaching) and in situations that are prone to errors. This in-depth understanding of the relationship between cognitive load, task demands and error occurrence is essential for the development of cognitive support systems to recognize and mitigate errors during complex surgical care in the operating room.

Intelligent Interruption Management System to Enhance Safety and Performance in Complex Surgical and Robotic Procedures.

Procedural flow disruptions secondary to interruptions play a key role in error occurrence during complex medical procedures, mainly because they increase mental workload among team members, negatively impacting team performance and patient safety. Since certain types of interruptions are unavoidable, and consequently the need for multitasking is inherent to complex procedural care, this field can benefit from an intelligent system capable of identifying in which moment flow interference is appropriate without generating disruptions. In the present study we describe a novel approach for the identification of tasks imposing low cognitive load and tasks that demand high cognitive effort during real-life cardiac surgeries. We used heart rate variability analysis as an objective measure of cognitive load, capturing data in a real-time and unobtrusive manner from multiple team members (surgeon, anesthesiologist and perfusionist) simultaneously. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the identification of specific steps, substeps and tasks that impose low cognitive load. An interruption management system can use these low demand situations to guide the surgical team in terms of the appropriateness of flow interruptions. The described approach also enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies) or in situations that are prone to errors. An in-depth understanding of the relationship between cognitive overload states, task demands, and error occurrence will drive the development of cognitive supporting systems that recognize and mitigate errors efficiently and proactively during high complex procedures.

Increasing patient safety and efficiency in transfusion therapy using formal process definitions.

The administration of blood products is a common, resource-intensive, and potentially problem-prone area that may place patients at elevated risk in the clinical setting. Much of the emphasis in transfusion safety has been targeted toward quality control measures in laboratory settings where blood products are prepared for administration as well as in automation of certain laboratory processes. In contrast, the process of transfusing blood in the clinical setting (ie, at the point of care) has essentially remained unchanged over the past several decades. Many of the currently available methods for improving the quality and safety of blood transfusions in the clinical setting rely on informal process descriptions, such as flow charts and medical algorithms, to describe medical processes. These informal descriptions, although useful in presenting an overview of standard processes, can be ambiguous or incomplete. For example, they often describe only the standard process and leave out how to handle possible failures or exceptions. One alternative to these informal descriptions is to use formal process definitions, which can serve as the basis for a variety of analyses because these formal definitions offer precision in the representation of all possible ways that a process can be carried out in both standard and exceptional situations. Formal process definitions have not previously been used to describe and improve medical processes. The use of such formal definitions to prospectively identify potential error and improve the transfusion process has not previously been reported. The purpose of this article is to introduce the concept of formally defining processes and to describe how formal definitions of blood transfusion processes can be used to detect and correct transfusion process errors in ways not currently possible using existing quality improvement methods.

Assessing the effectiveness of five process elicitation methods: A case study of chemotherapy treatment plan review.

To reduce the probability of failures and to improve outcomes of safety-critical human-intensive processes, such as health care processes, it is important to be able to rigorously analyze such processes. The quality of that analysis often depends on having an accurate, detailed, and sufficiently complete understanding of the process being analyzed, where this understanding is typically represented as a formal process model that could then drive various rigorous analysis approaches. Developing this understanding and the corresponding formal process model may be difficult and, thus, a variety of process elicitation methods are often used. The work presented in this paper evaluates the effectiveness of five common elicitation methods in terms of their ability to elicit detailed process information necessary to support rigorous process analysis. These methods are employed to elicit typical steps and steps for responding to exceptional situations in a safety-critical health care process, the chemotherapy treatment plan review process. The results indicate strengths and weaknesses of each of the elicitation methods and suggest that it is preferable to apply multiple elicitation methods.

Cognitive Support During High-Consequence Episodes of Care in Cardiovascular Surgery.

Despite significant efforts to reduce preventable adverse events in medical processes, such events continue to occur at unacceptable rates. This paper describes a computer science approach that uses formal process modeling to provide situationally aware monitoring and management support to medical professionals performing complex processes. These process models represent both normative and non-normative situations, and are validated by rigorous automated techniques such as model checking and fault tree analysis, in addition to careful review by experts. Context-aware Smart Checklists are then generated from the models, providing cognitive support during high-consequence surgical episodes. The approach is illustrated with a case study in cardiovascular surgery.

Divergent roles for Clusterin in Lung Injury and Repair.

Lung fibrosis is an unabated wound healing response characterized by the loss and aberrant function of lung epithelial cells. Herein, we report that extracellular Clusterin promoted epithelial cell apoptosis whereas intracellular Clusterin maintained epithelium viability during lung repair. Unlike normal and COPD lungs, IPF lungs were characterized by significantly increased extracellular Clusterin whereas the inverse was evident for intracellular Clusterin. In vitro and in vivo studies demonstrated that extracellular Clusterin promoted epithelial cell apoptosis while intercellular Clusterin modulated the expression of the DNA repair proteins, MSH2, MSH6, OGG1 and BRCA1. The fibrotic response in Clusterin deficient (CLU-/-) mice persisted after bleomycin and it was associated with increased DNA damage, reduced DNA repair responses, and elevated cellular senescence. Remarkably, this pattern mirrored that observed in IPF lung tissues. Together, our results show that cellular localization of Clusterin leads to divergent effects on epithelial cell regeneration and lung repair during fibrosis.

Analytic webs support the synthesis of ecological data sets.

A wide variety of data sets produced by individual investigators are now synthesized to address ecological questions that span a range of spatial and temporal scales. It is important to facilitate such syntheses so that "consumers" of data sets can be confident that both input data sets and synthetic products are reliable. Necessary documentation to ensure the reliability and validation of data sets includes both familiar descriptive metadata and formal documentation of the scientific processes used (i.e., process metadata) to produce usable data sets from collections of raw data. Such documentation is complex and difficult to construct, so it is important to help "producers" create reliable data sets and to facilitate their creation of required metadata. We describe a formal representation, an "analytic web," that aids both producers and consumers of data sets by providing complete and precise definitions of scientific processes used to process raw and derived data sets. The formalisms used to define analytic webs are adaptations of those used in software engineering, and they provide a novel and effective support system for both the synthesis and the validation of ecological data sets. We illustrate the utility of an analytic web as an aid to producing synthetic data sets through a worked example: the synthesis of long-term measurements of whole-ecosystem carbon exchange. Analytic webs are also useful validation aids for consumers because they support the concurrent construction of a complete, Internet-accessible audit trail of the analytic processes used in the synthesis of the data sets. Finally we describe our early efforts to evaluate these ideas through the use of a prototype software tool, SciWalker. We indicate how this tool has been used to create analytic webs tailored to specific data-set synthesis and validation activities, and suggest extensions to it that will support additional forms of validation. The process metadata created by SciWalker is readily adapted for inclusion in Ecological Metadata Language (EML) files.