Faculty Bibliography

The COVID-19 pandemic has significantly impacted families with young children (age 0-5). Using a subset of data from the randomized clinical trial of an integrated, preventive parenting model, Smart Beginnings (SB), this study examined associations between COVID-19-related school disruptions in early childhood education (ECE) and children's early elementary school outcomes. A secondary, exploratory aim sought to determine whether SB attenuated these relations. Path analyses demonstrated that school disruptions in ECE were associated with lower literacy skills at age 6 in letter-word identification (β=-.32, p<.01) and phonemic decoding (β=-.26, p<.05), but not for math or oral language skills. School disruptions in ECE were also related to increased internalizing behavior in children (β=.34, p<.01), with a trend for increased externalizing behavior (β=.22, p<.10). There was no significant moderation by SB intervention group. Implications for future school disruptions and acute stressors more broadly, as well as the role of preventive interventions, are discussed.

BACKGROUND:Moral distress, which occurs when the ethically correct action cannot be taken because of internal or external constraints, is associated with depression, burnout, and the desire to leave the healthcare profession among healthcare workers. This study compares internal medicine (IM) residents’ experiences of moral distress while caring for patients with COVID-19 in the year prior to and during the first year of the COVID-19 pandemic. METHODS:This is a mixed methods prospective observational cohort study that enrolled IM residents on a rolling basis beginning December 2018. Moral distress was evaluated via the validated Moral Distress Score-Revised (MDS-R) and Measure of Moral Distress for Healthcare Professionals (MDD-HP) and open-ended questions every 4-months via online surveys and through five resident focus groups. The moral distress scores (MDS) before and during the COVID-19 pandemic were compared using paired t-tests. Transcripts and free text were independently coded by investigators and analyzed by major themes and sub-themes. RESULTS: < .05). Qualitive findings included the exacerbation of existing moral distress and the emergence of new drivers of moral distress, including personal protective equipment, visitor policies, lack of moral framework, and tension between protecting one’s own health and caring for others. CONCLUSIONS:The results of this preliminary analysis suggest that the COVID-19 pandemic exacerbated pre-existing experiences of moral distress and brought to light new and different morally distressing situations for trainees. This analysis of the impact of the pandemic is valuable not only for identifying leverage points for intervention, but also for informing future crisis preparedness and cultivating moral resilience in trainees and the healthcare workforce. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1186/s12910-025-01274-6.

RAGE and its intracellular effector molecule, the actin polymerase DIAPH1, mediate inflammation and the complications of diabetes. Using NMR spectroscopy and mass spectrometry, we built a structural model of the RAGE-DIAPH1 complex, revealing how binding of the cytoplasmic tail of RAGE (ctRAGE) to DIAPH1 stimulates its actin polymerization activity, which is inhibited by a small molecule antagonist of RAGE-DIAPH1 interaction, RAGE406R. The solution structure of the RAGE406R - ctRAGE suggests that RAGE406R prevents the formation of the RAGE-DIAPH1. FRET, actin polymerization assays, smooth muscle cell migration, and THP1 cell inflammation experiments, together with the in vivo interrogation of the effects of RAGE406R in mouse models of inflammation and diabetic wound healing, support this mode of RAGE-DIAPH1 antagonism. Finally, the treatment of macrophages differentiated from peripheral blood-derived mononuclear cells from humans with type 1 diabetes with RAGE406R reduces the mRNA expression of the chemokine CCL2, diminishing the expression of a key node in the inflammatory response.

We conducted an umbrella review to synthesize the evidence on the diagnostic performance of liquid biopsy tests for detection of head and neck squamous cell carcinoma (HNSCC). Systematic reviews (SRs) were searched in Medline, Embase, and Google Scholar through December 6, 2023. The Joanna Briggs Institute Critical Appraisal Tool for Systematic Reviews was used to assess methodological quality. Two independent reviewers extracted data. We examined the pooled sensitivity and specificity of biomarker classes. We also statistically pooled sensitivity and specificity of individual biomarkers for oral SCC in cases where meta-analysis was not yet published, since most HNSCC occurs in the oral cavity. Performance was also assessed by specimen type (saliva, serum, plasma, and whole blood). Thirty-one SRs met inclusion criteria and 21 included meta-analyses on transcriptomic, proteomic, genomic, or metabolomic biomarkers. Overall methodologic quality was moderate to high. Primary study overlap was ≥ 15 % in 9.3 % of SR pairwise comparisons. MicroRNA (miRNA) was the biomarker class represented in the most SRs (n = 19) and individual studies (n = 106). Among these, the highest sensitivity was 77 % (95 % CI, 68-84 %), observed in miRNA-21. Hypermethylated DNA was the biomarker class with the highest pooled sensitivity (86 %; 95 % CI, 60-96 %) and specificity (92 %; 95 % CI, 80-97 %) overall, and with superior performance when used in panels compared to individual markers. In studies focused on OSCC detection, no other biomarker class or fluid type demonstrated superior performance over others. In future clinical studies, panels including hypermethylated DNA merit more rigorous evaluation to establish high specificity in addition to sufficient sensitivity.

BACKGROUND:Childhood obesity disproportionately affects priority populations, including racial and ethnic minority groups and those with lower socio-economic backgrounds. These groups often encounter barriers to accessing public health services and may benefit from targeted interventions. OBJECTIVE:This scoping review aimed to identify the characteristics of populations involved in interventions to prevent early childhood obesity and to understand whether and how existing interventions targeted and reached priority populations. METHODS:Databases and trial registries were systematically searched until 4 October 2024, for planned, ongoing, and completed randomised controlled trials evaluating parent-focussed, behavioural interventions for childhood obesity prevention, starting within the first year of life. Two reviewers independently extracted data using a customised tool. RESULTS:Of the 11 960 articles identified, 82 trials were eligible. Most trials (87%) were conducted (or planned) in high-income countries, 11% in upper middle-income countries, and 2% in lower middle-income countries. Priority populations included parent-child dyads from specific ethnic or racial groups facing psychological, social, and/or economic disadvantages. Among the completed trials, 54% targeted priority populations, yet only 33% exclusively enrolled participants from these groups. Additionally, less than a quarter of the trials involved priority populations in the design of interventions (17%) and developed tailored interventions for these groups (21%). CONCLUSIONS:Current interventions do not sufficiently target, reach and engage priority populations. To achieve health equity in early childhood obesity prevention, it is essential to include underserved and at-risk populations in research and intervention design.

Artificial intelligence (AI) applications for radiology workflow have the potential to improve patient and health-system-level outcomes through more efficient and accurate diagnosis and clinical decision making. For a variety of time-intensive steps, numerous types of applications are now available with variable reported measures and degrees of success. The tools we highlight aim to accelerate imaging acquisition, reduce cognitive and manual burden on radiologists and others involved in the care pathway, improve diagnostic accuracy, and shorten the time to clinical action based on imaging results. Most existing studies have focused on intermediate outcomes, such as task duration or time to the next step in care. In this article, we present an examination of AI applications across the medical imaging exam workflow, review examples of real-world evidence on these tools, and summarize the relevant performance metrics by application type. Beyond the more immediately acquired measures, to demonstrate benefit to patient health and economic outcomes, a more integrated assessment is necessary, and in an iterative fashion. To evolve beyond early workflow gains, interoperable tools must be tied to measurable downstream impacts, such as reduced disease severity, lower mortality, and shorter hospital stays, while we acknowledge that current empirical evaluations are limited.

OBJECTIVES/OBJECTIVE:To examine (1) trends in the incidence and duration of Medicare opt-outs among urologic surgeons, (2) the demographic and professional characteristics of urologists opting out, and (3) the surgeon-level predictors associated with the timing of Medicare opt-outs. METHODS:This retrospective study analyzed data from the Centers for Medicare & Medicaid Services (CMS) Opt-Out Affidavits. Surgeon-level data were linked to public professional profiles using National Provider Identifiers to extract information on demographics, training, years in practice, practice type, subspecialty, and geographic location. RESULTS:The incidence of Medicare opt-outs among urologic surgeons remained low between 2012 and 2025, averaging 3.9 opt-outs per year (n=51). Most opt-outs were male (92.2%) generalists (64.7%) in independent practice settings (54.9%) with more than 30 years of experience (56.9%). Opt-out lengths significantly declined over time, from an average of 5113.5 days in 2012 to 730.5 days in 2025. Predictors of later opt-out included female sex (+2.4 years), fewer years in practice (+3.6 years for <19 years), and subspecialty in female urology (+4.8 years) or sexual medicine (+2.3 years). In contrast, earlier opt-out was associated with academic affiliation (-2.3 years) and subspecialty in male infertility (-4.8 years) or urologic oncology (-4.6 years). CONCLUSIONS:Although Medicare opt-outs remain rare among urologic surgeons, temporal trends reveal shortening durations of opt-out and distinct demographic and practice-related patterns in participation. These findings underscore the need for targeted efforts to support late-career and independently practicing urologists, while addressing evolving payment structures and retention strategies within Medicare to maintain workforce engagement. LEVEL OF EVIDENCE/METHODS:Level III.

BACKGROUND:Glaucoma Research Foundation's third Catalyst for a Cure team (CFC3) was established in 2019 to uncover new therapies for glaucoma, a leading cause of blindness. In the 2021 meeting "Solving Neurodegeneration," (detailed in Mol Neurodegeneration 17(1), 2022) the team examined the failures of investigational monotherapies, issues with translatability, and other significant challenges faced when working with neurodegenerative disease models. They emphasized the need for novel, humanized models and proposed identifying commonalities across neurodegenerative diseases to support the creation of pan-neurodegenerative disease therapies. Since then, the fourth Catalyst for a Cure team (CFC4) was formed to explore commonalities between glaucoma and other neurodegenerative diseases. This review summarizes outcomes from the 2023 "Solving Neurodegeneration 2" meeting, a forum for CFC3 and CFC4 to share updates, problem solve, plan future research collaborations, and identify areas of unmet need or opportunity in glaucoma and the broader field of neurodegenerative disease research. MAIN BODY/METHODS:We summarize the recent progress in the field of neurodegenerative disease research and present the newest challenges and opportunities moving forward. While translatability and disease complexity continue to pose major challenges, important progress has been made in identifying neuroprotective targets and understanding neuron-glia-vascular cell interactions. New challenges involve improving our understanding of the disease microenvironment and timeline, identifying the optimal approach(es) to neuronal replacement, and finding the best drug combinations and synergies for neuroprotection. We propose solutions to common research questions, provide prescriptive recommendations for future studies, and detail methodologies, strategies, and approaches for addressing major challenges at the forefront of neurodegenerative disease research. CONCLUSIONS:This review is intended to serve as a research framework, offering recommendations and approaches to validating neuroprotective targets, investigating rare cell types, performing cell-specific functional characterizations, leveraging novel adaptations of scRNAseq, and performing single-cell sorting and sequencing across neurodegenerative diseases and disease models. We focus on modeling neurodegeneration using glaucoma and other neurodegenerative pathologies to investigate the temporal and spatial dynamics of neurodegenerative disease pathogenesis, suggesting researchers aim to identify pan-neurodegenerative drug targets and drug combinations leverageable across neurodegenerative diseases.