Faculty Bibliography

INTRODUCTION/BACKGROUND:It is unclear how early neuronal deficits occur in tauopathies, if these are associated with changes in neuronal network activity, and if they can be alleviated with therapies. METHODS:imaging in tauopathy mice at 6 versus 12 months, compared to controls, and treated the younger animals with a tau antibody. RESULTS:Neuronal function was impaired at 6 months but did not deteriorate further at 12 months, presumably because cortical tau burden was comparable at these ages. At 6 months, neurons were mostly hypoactive, with enhanced neuronal synchrony, and had dysregulated responses to stimulus. Ex vivo, electrophysiology revealed altered synaptic transmission and enhanced excitability of motor cortical neurons, which likely explains the altered network activity. Acute tau antibody treatment reduced pathological tau and gliosis and partially restored neuronal function. DISCUSSION/CONCLUSIONS:Tauopathies are associated with early neuronal deficits that can be attenuated with tau antibody therapy. HIGHLIGHTS/CONCLUSIONS:Neuronal hypofunction in awake and behaving mice in early stages of tauopathy. Altered network activity disrupted local circuitry engagement in tauopathy mice. Enhanced neuronal excitability and altered synaptic transmission in tauopathy mice. Tau antibody acutely reduced soluble phospho-tau and improved neuronal function.

Although the role of the medial temporal lobe (MTL) and the hippocampus in episodic memory is well established, there is emerging evidence that these regions play a broader role in cognition, specifically in temporal processing. However, despite strong evidence that the hippocampus plays a critical role in sequential processing, the involvement of the MTL in timing per se is poorly understood. In the present study, we investigated whether patients with MTL damage exhibit differential performance on a temporal distance memory task. Critically, we manipulated context shifts, or boundaries, which have been shown to interfere with associative binding, leading to increases in subjective temporal distance. We predicted that patients with MTL damage would show impaired binding across boundaries and thus fail to show temporal expansion. Consistent with this hypothesis, unilateral patients failed to show a temporal expansion effect, and bilateral patients actually exhibited the reverse effect, suggesting a critical role for the MTL in binding temporal information across boundaries. Furthermore, patients were impaired overall on both the temporal distance memory task and recognition memory, but not on an independent, short-timescale temporal perception task. Interestingly, temporal distance performance could be independently predicted by performance on recognition memory and the short temporal perception task. Together, these data suggest that distinct mnemonic and temporal processes may influence long interval temporal memory and that damage to the MTL may impair the ability to integrate episodic and temporal information in memory.

Mediation analysis is appealing for its ability to improve understanding of the mechanistic drivers of causal effects, but real-world data complexities challenge its successful implementation, including (i) the existence of post-exposure variables that also affect mediators and outcomes (thus, confounding the mediator-outcome relationship), that may also be (ii) multivariate, and (iii) the existence of multivariate mediators. All three challenges are present in the mediation analysis we consider here, where our goal is to estimate the indirect effects of receiving a Section 8 housing voucher as a young child on the risk of developing a psychiatric mood disorder in adolescence that operate through mediators related to neighborhood poverty, the school environment, and instability of the neighborhood and school environments, considered together and separately. Interventional direct and indirect effects (IDE/IIE) accommodate post-exposure variables that confound the mediator-outcome relationship, but currently, no readily implementable nonparametric estimator for IDE/IIE exists that allows for both multivariate mediators and multivariate post-exposure intermediate confounders. The absence of such an IDE/IIE estimator that can easily accommodate both multivariate mediators and post-exposure confounders represents a significant limitation for real-world analyses, because when considering each mediator subgroup separately, the remaining mediator subgroups (or a subset of them) become post-exposure intermediate confounders. We address this gap by extending a recently developed nonparametric estimator for the IDE/IIE to allow for easy incorporation of multivariate mediators and multivariate post-exposure confounders simultaneously. We apply the proposed estimation approach to our analysis, including walking through a strategy to account for other, possibly co-occurring intermediate variables when considering each mediator subgroup separately.

Recent studies have documented prolonged expression of viral antigens and RNA and associated inflammation after infection with SARS-CoV-2 in a substantial proportion of infected patients. The persisting SARS-CoV-2 effects and findings, with inflammation associated with continued detection of viral antigens, especially resemble those previously reported for influenza virus, as well as respiratory syncytial virus (RSV). The reports indicate the need for improved insight into the mechanisms whereby post-SARS-CoV-2 infection-related illness is apparently more common and perhaps even more persistent after infection than observed for other respiratory viruses.

Competency-based medical education (CBME) has produced large collections of data, which can provide valuable information about trainees and medical education systems. Many organizations continue to struggle with accessing, collecting, governing, analyzing, and visualizing their clinical and/or educational data. This hinders data sharing efforts within and across organizations, which are foundational in supporting system-wide improvements. Challenges to data sharing within medical education include variability in legislation, existing data policies, heterogeneity of data, inadequate data infrastructure, and various intended purposes or uses. In this eye opener, the authors describe four case studies to illustrate some of the aforementioned challenges and characterize the complexity of data sharing within medical education along two dimensions: organizational (single vs. multiple) and data type (clinical and/or educational). With the goal of better supporting data sharing initiatives, the authors introduce an action-oriented blueprint that includes a three-stage process (i.e., preparation, execution, and iteration) to highlight crucial aspects of data sharing. This evidence-informed model incorporates current best practices and aims to support data sharing initiatives within their own organizations and across multiple organizations. Finally, organizations can use this model to conceptually guide and track their progression throughout the data sharing process.

BACKGROUND/UNASSIGNED:Despite a shortage of potential donors for heart transplant in the United States, most potential donor hearts are discarded. We evaluated predictors of donor heart acceptance in the United States and applied machine learning methods to improve prediction. METHODS/UNASSIGNED:We included a nationwide (2005-2020) cohort of potential heart donors in the United States (n=73 948) from the Scientific Registry of Transplant Recipients and a more recent (2015-2020) rigorously phenotyped cohort of potential donors from DHS (Donor Heart Study; n=4130). We identified predictors of acceptance for heart transplant in both cohorts using multivariate logistic regression, incorporating time-interaction terms to characterize their varying effects over time. We fit models predicting acceptance for transplant in a 50% training subset of DHS using logistic regression, least absolute shrinkage and selection operator, and random forest algorithms and compared their performance in the remaining 50% (test) of the subset. RESULTS/UNASSIGNED:value for time interaction, <0.05 for all). A random forest model (area under the curve, 0.908; accuracy, 0.831) outperformed other prediction algorithms in the test subset and was used as the basis of a novel web-based prediction tool. CONCLUSIONS/UNASSIGNED:Predictors of donor heart acceptance for transplantation have changed significantly over the last 2 decades, likely reflecting evolving evidence regarding their impact on posttransplant outcomes. Real-time prediction of donor heart acceptance, using our web-based tool, may improve efficiency during donor management and heart allocation.

Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.

Current dermatology residency education may be deficient in curricular topics and training related to diversity, equity, and inclusion (DEI). Integrating more DEI topics within residency curricula may improve clinical care delivered to diverse populations and improve cultural humility among trainees. The objective of this electronic Delphi (e-Delphi) study was to reach a consensus on the most important DEI topics for inclusion in dermatology residency program curricula nationwide. Sixty-one DEI-related topics were proposed by an expert panel consisting of dermatologists from the Association of Professors of Dermatology DEI subcommittee and the American Academy of Dermatology Diversity Task Force. Two rounds of anonymous electronic surveys based on a 5-point Likert scale were administered using a modified e-Delphi design. Voluntary participants including residents and academic dermatologists were self-selected after an email was sent to the Association of Professors of Dermatology listserve.

BACKGROUND:The inability of biologics to pass the plasma membrane prevents their development as therapeutics for intracellular targets. To address the lack of methods for cytosolic protein delivery, we used the type III secretion system (T3SS) of Y. enterocolitica, which naturally injects bacterial proteins into eukaryotic host cells, to deliver monobody proteins into cancer cells. Monobodies are small synthetic binding proteins that can inhibit oncogene signaling in cancer cells with high selectivity upon intracellular expression. Here, we engineered monobodies targeting the BCR::ABL1 tyrosine kinase for efficient delivery by the T3SS, quantified cytosolic delivery and target engagement in cancer cells and monitored inhibition of BCR::ABL1 signaling. METHODS:In vitro assays were performed to characterize destabilized monobodies (thermal shift assay and isothermal titration calorimetry) and to assess their secretion by the T3SS. Immunoblot assays were used to study the translocation of monobodies into different cell lines and to determine the intracellular concentration after translocation. Split-Nanoluc assays were performed to understand translocation and degradation kinetics and to evaluate target engagement after translocation. Phospho flow cytometry and apoptosis assays were performed to assess the functional effects of monobody translocation into BCR:ABL1-expressing leukemia cells. RESULTS:To enable efficient translocation of the stable monobody proteins by the T3SS, we engineered destabilized mutant monobodies that retained high affinity target binding and were efficiently injected into different cell lines. After injection, the cytosolic monobody concentrations reached mid-micromolar concentrations considerably exceeding their binding affinity. We found that injected monobodies targeting the BCR::ABL1 tyrosine kinase selectively engaged their target in the cytosol. The translocation resulted in inhibition of oncogenic signaling and specifically induced apoptosis in BCR::ABL1-dependent cells, consistent with the phenotype when the same monobody was intracellularly expressed. CONCLUSION/CONCLUSIONS:Hence, we establish the T3SS of Y. enterocolitica as a highly efficient protein translocation method for monobody delivery, enabling the selective targeting of different oncogenic signaling pathways and providing a foundation for future therapeutic application against intracellular targets.