Smartphone-Based Gait Cadence to Identify Older Adults with Decreased Functional Capacity.

Background: Functional capacity assessment is a critical step in the preoperative evaluation to identify patients at increased risk of cardiac complications and disability after major noncardiac surgery. Smartphones offer the potential to objectively measure functional capacity but are limited by inaccuracy in patients with poor functional capacity. Open-source methods exist to analyze accelerometer data to estimate gait cadence (steps/min), which is directly associated with activity intensity. Here, we used an updated Step Test smartphone application with an open-source method to analyze accelerometer data to estimate gait cadence and functional capacity in older adults. Methods: We performed a prospective observational cohort study within the Frailty, Activity, Body Composition and Energy Expenditure in Aging study at the University of Chicago. Participants completed the Duke Activity Status Index (DASI) and performed an in-clinic 6-min walk test (6MWT) while using the Step Test application on a study smartphone. Gait cadence was measured from the raw accelerometer data using an adaptive empirical pattern transformation method, which has been previously validated. A 6MWT distance of 370 m was used as an objective threshold to identify patients at high risk. We performed multivariable logistic regression to predict walking distance using a priori explanatory variables. Results: Sixty patients were enrolled in the study. Thirty-seven patients completed the protocol and were included in the final data analysis. The median (IQR) age of the overall cohort was 71 (69-74) years, with a body mass index of 31 (27-32). There were no differences in any clinical characteristics or functional measures between participants that were able to walk 370 m during the 6MWT and those that could not walk that distance. Median (IQR) gait cadence for the entire cohort was 110 (102-114) steps/min during the 6MWT. Median (IQR) gait cadence was higher in participants that walked more than 370 m during the 6MWT 112 (108-118) versus 106 (96-114) steps/min; p = 0.0157). The final multivariable model to identify participants that could not walk 370 m included only median gait cadence. The Youden's index cut-point was 107 steps/min with a sensitivity of 0.81 (95% CI: 0.77, 0.85) and a specificity of 0.57 (95% CI: 0.55, 0.59) and an AUCROC of 0.69 (95% CI: 0.51, 0.87). Conclusions: Our pilot study demonstrates the feasibility of using gait cadence as a measure to estimate functional capacity. Our study was limited by a smaller than expected sample size due to COVID-19, and thus, a prospective study with preoperative patients that measures outcomes is necessary to validate our findings.

Improved integration of single-cell transcriptome and surface protein expression by LinQ-View

Summary Multimodal advances in single-cell sequencing have enabled the simultaneous quantification of cell surface protein expression alongside unbiased transcriptional profiling. Here, we present LinQ-View, a toolkit designed for multimodal single-cell data visualization and analysis. LinQ-View integrates transcriptional and cell surface protein expression profiling data to reveal more accurate cell heterogeneity and proposes a quantitative metric for cluster purity assessment. Through comparison with existing multimodal methods on multiple public CITE-seq datasets, we demonstrate that LinQ-View efficiently generates accurate cell clusters, especially in CITE-seq data with routine numbers of surface protein features, by preventing variations in a single surface protein feature from affecting results. Finally, we utilized this method to integrate single-cell transcriptional and protein expression data from SARS-CoV-2-infected patients, revealing antigen-specific B cell subsets after infection. Our results suggest LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations (e.g., B cells). Graphical Highlights • LinQ-View integrates mRNA and protein expression data to reveal cell heterogeneity• LinQ-View prevents single dominant ADT features from affecting clustering• LinQ-View presents a quantitative purity metric for CITE-seq data• LinQ-View is specialized in handling CITE-seq data with fewer ADT features Motivation Multimodal single-cell sequencing enables multiple aspects for characterizing the dynamics of cell states and developmental processes. Properly integrating information from multiple modalities is a crucial step for interpreting cell heterogeneity. Here, we present LinQ-View, a computational workflow that provides an effective solution for integrating multiple modalities of CITE-seq data for downstream interpretation. LinQ-View balances information from multiple modalities to achieve accurate clustering results and is specialized in handling CITE-seq data with routine numbers of surface protein features. Li et al. present LinQ-View, a computational workflow that provides an effective solution for integrating multiple modalities of CITE-seq data and quantitative assessment of cluster purity. LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations.

Pulmonary Parenchymal Changes in COVID-19 Survivors.

BACKGROUND: As the COVID-19 pandemic moves into the survivorship phase, questions regarding long-term lung damage remain unanswered. Previous histopathologic studies are limited to autopsy reports. We studied lung specimens from COVID-19 survivors who underwent elective lung resections to determine whether postacute histopathologic changes are present. METHODS: This multicenter observational study included 11 adult COVID-19 survivors who had recovered but subsequently underwent unrelated elective lung resection for indeterminate lung nodules or lung cancer. We compared these against an age- and procedure-matched control group who never contracted COVID-19 (n = 5) and an end-stage COVID-19 group (n = 3). A blinded pulmonary pathologist examined the lung parenchyma focusing on 4 compartments: airways, alveoli, interstitium, and vasculature. RESULTS: Elective lung resection was performed in 11 COVID-19 survivors with asymptomatic (n = 4), moderate (n = 4), and severe (n = 3) COVID-19 infections at a median 68.5 days (range 24-142 days) after the COVID-19 diagnosis. The most common operation was lobectomy (75%). Histopathologic examination identified no differences between the lung parenchyma of COVID-19 survivors and controls across all compartments examined. Conversely, patients in the end-stage COVID-19 group showed fibrotic diffuse alveolar damage with intra-alveolar macrophages, organizing pneumonia, and focal interstitial emphysema. CONCLUSIONS: In this study to examine the lung parenchyma of COVID-19 survivors, we did not find distinct postacute histopathologic changes to suggest permanent pulmonary damage. These results are reassuring for COVID-19 survivors who recover and become asymptomatic.

Improved integration of single-cell transcriptome and surface protein expression by LinQ-View.

Multimodal advances in single-cell sequencing have enabled the simultaneous quantification of cell surface protein expression alongside unbiased transcriptional profiling. Here, we present LinQ-View, a toolkit designed for multimodal single-cell data visualization and analysis. LinQ-View integrates transcriptional and cell surface protein expression profiling data to reveal more accurate cell heterogeneity and proposes a quantitative metric for cluster purity assessment. Through comparison with existing multimodal methods on multiple public CITE-seq datasets, we demonstrate that LinQ-View efficiently generates accurate cell clusters, especially in CITE-seq data with routine numbers of surface protein features, by preventing variations in a single surface protein feature from affecting results. Finally, we utilized this method to integrate single-cell transcriptional and protein expression data from SARS-CoV-2-infected patients, revealing antigen-specific B cell subsets after infection. Our results suggest LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations (e.g., B cells).

Profiling B cell immunodominance after SARS-CoV-2 infection reveals antibody evolution to non-neutralizing viral targets.

Dissecting the evolution of memory B cells (MBCs) against SARS-CoV-2 is critical for understanding antibody recall upon secondary exposure. Here, we used single-cell sequencing to profile SARS-CoV-2-reactive B cells in 38 COVID-19 patients. Using oligo-tagged antigen baits, we isolated B cells specific to the SARS-CoV-2 spike, nucleoprotein (NP), open reading frame 8 (ORF8), and endemic human coronavirus (HCoV) spike proteins. SARS-CoV-2 spike-specific cells were enriched in the memory compartment of acutely infected and convalescent patients several months post symptom onset. With severe acute infection, substantial populations of endemic HCoV-reactive antibody-secreting cells were identified and possessed highly mutated variable genes, signifying preexisting immunity. Finally, MBCs exhibited pronounced maturation to NP and ORF8 over time, especially in older patients. Monoclonal antibodies against these targets were non-neutralizing and non-protective in vivo. These findings reveal antibody adaptation to non-neutralizing intracellular antigens during infection, emphasizing the importance of vaccination for inducing neutralizing spike-specific MBCs.

Nanotraps for the containment and clearance of SARS-CoV-2.

SARS-CoV-2 enters host cells through its viral spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptors on the host cells. Here, we show that functionalized nanoparticles, termed "Nanotraps," completely inhibited SARS-CoV-2 infection by blocking the interaction between the spike protein of SARS-CoV-2 and the ACE2 of host cells. The liposomal-based Nanotrap surfaces were functionalized with either recombinant ACE2 proteins or anti-SARS-CoV-2 neutralizing antibodies and phagocytosis-specific phosphatidylserines. The Nanotraps effectively captured SARS-CoV-2 and completely blocked SARS-CoV-2 infection to ACE2-expressing human cell lines and primary lung cells; the phosphatidylserine triggered subsequent phagocytosis of the virus-bound, biodegradable Nanotraps by macrophages, leading to the clearance of pseudotyped and authentic virus in vitro. Furthermore, the Nanotraps demonstrated an excellent biosafety profile in vitro and in vivo. Finally, the Nanotraps inhibited pseudotyped SARS-CoV-2 infection in live human lungs in an ex vivo lung perfusion system. In summary, Nanotraps represent a new nanomedicine for the inhibition of SARS-CoV-2 infection.

Fair and equitable subject selection in concurrent COVID-19 clinical trials.

Clinical trials emerged in rapid succession as the COVID-19 pandemic created an unprecedented need for life-saving therapies. Fair and equitable subject selection in clinical trials offering investigational therapies ought to be an urgent moral concern. Subject selection determines the distribution of risks and benefits, and impacts the applicability of the study results for the larger population. While Research Ethics Committees monitor fair subject selection within each trial, no standard oversight exists for subject selection across multiple trials for the same disease. Drawing on the experience of multiple clinical trials at a single academic medical centre in the USA, we posit that concurrent COVID-19 trials are liable to unfair and inequitable subject selection on account of scientific uncertainty, lack of transparency, scarcity and, lastly, structural barriers to equity compounded by implicit bias. To address the critical gap in the current literature and international regulation, we propose new ethical guidelines for research design and conduct that bolsters fair and equitable subject selection. Although the proposed guidelines are tailored to the research design and protocol of concurrent trials in the COVID-19 pandemic, they may have broader relevance to single COVID-19 trials.

SARS-CoV-2 Infection Severity Is Linked to Superior Humoral Immunity against the Spike.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity of the antibody response mounted against this novel virus is not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and nonstructural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.IMPORTANCE With the ongoing pandemic, it is critical to understand how natural immunity against SARS-CoV-2 and COVID-19 develops. We have identified that subjects with more severe COVID-19 disease mount a more robust and neutralizing antibody response against SARS-CoV-2 spike protein. Subjects who mounted a larger response against the spike also mounted antibody responses against other viral antigens, including the nucleocapsid protein and ORF8. Additionally, this study reveals that subjects with more severe disease mount a larger memory B cell response against the spike. These data suggest that subjects with more severe COVID-19 disease are likely better protected from reinfection with SARS-CoV-2.

Distinct B cell subsets give rise to antigen-specific antibody responses against SARS-CoV-2.

Discovery of durable memory B cell (MBC) subsets against neutralizing viral epitopes is critical for determining immune correlates of protection from SARS-CoV-2 infection. Here, we identified functionally distinct SARS-CoV-2-reactive B cell subsets by profiling the repertoire of convalescent COVID-19 patients using a high-throughput B cell sorting and sequencing platform. Utilizing barcoded SARS-CoV-2 antigen baits, we isolated thousands of B cells that segregated into discrete functional subsets specific for the spike, nucleocapsid protein (NP), and open reading frame (ORF) proteins 7a and 8. Spike-specific B cells were enriched in canonical MBC clusters, and monoclonal antibodies (mAbs) from these cells were potently neutralizing. By contrast, B cells specific to ORF8 and NP were enriched in naïve and innate-like clusters, and mAbs against these targets were exclusively non-neutralizing. Finally, we identified that B cell specificity, subset distribution, and affinity maturation were impacted by clinical features such as age, sex, and symptom duration. Together, our data provide a comprehensive tool for evaluating B cell immunity to SARS-CoV-2 infection or vaccination and highlight the complexity of the human B cell response to SARS-CoV-2.