United States

Background
Chronic orthopedic conditions such as arthritis often require specialist care to prevent long term complications. Children with arthritis have an increased risk of fracture, medication-induced complications and long-term emotional and social dysfunctions. However, according to the Arthritis Foundation, remission is possible in these children with early diagnosis and aggressive treatment. The objective of this study is to use National Survey of Children’s Health (NSCH) data to identify long-term implications due to difficulties accessing specialist care in children with arthritis.

Methods
This retrospective study utilized 2020-2021 NSCH data to evaluate whether children with arthritis had difficulties obtaining specialist care and the implications. All children with arthritis were stratified by demographic variables including age, sex and race. Multivariable logistic regression was used to compare children who faced challenges receiving specialist care with those who did not and the effect on their daily activities.

Results
A total of 113 children with arthritis who required access to specialty care were identified according to the study criteria. Most cases of arthritis presented in females (n= 73) with a median age of 15.1 years old. Out of the 113 children requiring specialty care, 37 of them had insufficient access to the needed care. Children with difficulty accessing specialist care were more likely to have interruptions in their daily activities with a Coefficient of 0.369 (95% Confidence Interval: 0.161 to 0.677; p=0.001).

Conclusion
This study faces limitations due to its small sample size. However, an overwhelming majority of the respondents that experienced difficulty receiving care for juvenile arthritis reported subsequent disruptions in daily activities. This underscores the need for future studies examining the barriers hindering certain children from obtaining specialist care. Understanding the root causes can facilitate the development of strategies to enhance specialist care accessibility, thereby improving outcomes for children with arthritis.

AMA Research Challenge 2025 

Health Equity and Childhood Arthritis: Barriers to Specialist Care and the Long-Term Impact on Daily Life

This annual scholarly program is designed to provide undergraduate students with a structured introduction to laboratory research within their home institution. Participants are matched with principal investigators and mentored by graduate students, enabling them to engage directly in ongoing research projects and develop foundational skills in scientific inquiry.

Indicium 2025

This annual scholarly program is designed to provide undergraduate students with a structured introduction to laboratory research within their home institution.
This year’s cohort focused on projects in the field of longevity science, exploring diverse topics such as bioinformatics, molecular biology, and cognitive science.

poster

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Join the AMA Research Challenge poster symposium and semifinals to explore top research posters and score posters in the semifinals (an AMA member exclusive opportunity).

Background:
People experiencing homelessness face profound barriers to accessing palliative and end-of-life care, including stigma, fragmented services, and the lack of stable housing for hospice visits. As a result, many unhoused individuals die without comfort-focused care, social support, or dignity. Rocky Mountain Refuge (RMR) in Denver, Colorado, is one of only a handful of programs in the U.S. offering hospice support specifically for this population. By creating a safe space for those experiencing homelessness at the end of life, RMR fills a critical gap and offers lessons for advancing health equity in palliative care.

Methods:
Between February and October 2025, an internal evaluation of Rocky Mountain Refuge (RMR) was conducted using stakeholder surveys and qualitative interviews. The objective of this study was to evaluate RMR's unique care model to: a) inform program improvement and b) lay the foundation for a scalable model. Sixty stakeholders were invited to complete an online survey (24 responses, 40% response rate), and five qualitative interviews were conducted with supporters and donors. These participants were selected for their insight into RMR’s mission, operations, and sustainability. All qualitative data were analyzed using Braun and Clarke’s six-phase thematic analysis framework. 

Results:
Six key themes emerged: (1) Mission and dignity: RMR restores humanity and respect to those often excluded from end-of-life care; (2) Awareness and understanding: public misconceptions and discomfort surrounding death and homelessness hinder engagement; (3) Operational and financial challenges: limited capacity and funding instability constrain sustainability; (4) Policy and political context: funding and regulations create uncertainty in a shifting landscape; (5) Community trust and connection: personal relationships and in-person engagement foster understanding and support; and (6) Visibility and impact: storytelling, data sharing, and partnerships strengthen awareness and credibility.

Conclusions:
RMR represents an innovative, equity-driven model that restores dignity at the end of life for unhoused individuals. Findings highlight both the moral urgency and systemic challenges of sustaining such programs and underscore the importance of storytelling, community engagement, and policy navigation to advance equitable hospice and palliative care.

Dignity in Death: Evaluating a Unique End of Life Care Model that Bridges Hospice and Homelessness

Introduction 
Significant racial disparities in survival outcomes exist among Head and Neck Cancer (HNC) patients. Appropriate racial representation in clinical trials is essential to evaluate whether head and neck cancer (HNC) treatments are effective across diverse populations. Building upon a previous analysis by Zuckerman et al., that reported racial and ethnic disparity in HNC clinical trials, this current study assessed temporal changes in HNC clinical trial enrollment in the context of changing racial and ethnic disease prevalence between 2002 and 2020. 

Methods 
A comprehensive review of clinical trials focusing on HNC from January 2002 to December 2020 yielded 278 initial studies. After applying inclusion and exclusion criteria, 107 eligible trials were analyzed. Participant demographics were categorized into five standardized racial/ethnic groups aligned with the Surveillance, Epidemiology, and End Results (SEER) database classifications. Differences in racial group enrollment rates (as compared to their representation among HNC patients) were investigated using boxplots and scatterplots stratified by race and year, and with multiple linear regression.

Results 
Significant racial disparities in HNC clinical trials were identified, where White participants were overrepresented and minority groups, including Black (-0.121, 95% CI: [-0.145, -0.095]), Hispanic (-0.174, 95% CI: [-0.199, -0.149]), Asian/Pacific Islander (-0.129, 95% CI: [-0.155, -0.105]), and American Indian/Alaska Native (-0.104, 95% CI: [-0.128, -0.079]), were consistently underrepresented, with no change in representation over 18 years time period. This suggests that while previous analysis of this data had shown worsening of racial and ethnic diversity over time. This analysis examined these temporal changes in the context of changing disease prevalence, and illustrated stable enrollment proportions over time. 

Conclusion 
This work builds on work by Zuckerman et al. by adjusting for HNC patient demographics and by assessing annual changes in racial representation. This methodology revealed that there was no change in racial HNC trial representation over the last 20 years. It also reinforces the work by Zuckerman et al. by demonstrating that initiatives to ensure equitable representation are not working. In both studies, there was persistent over-representation of white HNC patients in HNC clinical trials. New approaches that facilitate equitable representation are needed to improve the generalizability and effectiveness of HNC treatment outcomes across all demographic groups.

Racial Disparities Between Head and Neck Cancer Clinical Trials and Head and Neck Cancer Patients in the United States: A Retrospective Study

Background 
Asthma is the most prevalent chronic illness in children worldwide, contributing to significant morbidity, healthcare utilization, and economic burden. In the United States, approximately 5 million children are currently affected. This review examines the environmental context and lifestyle determinants influencing pediatric asthma globally and within the U.S., with a special emphasis upon the Inland Empire (IE) in Southern California. The IE’s unique geographic landscape and role as a major transportation hub highlights its critical role for understanding how both environmental and structural factors exacerbate asthma burden in the IE pediatric population. 

Methods 
A narrative literature review and regional data analysis were conducted to identify environmental, socioeconomic, and healthcare accessibility factors behind pediatric asthma in the IE. PubMed, Scopus, and Google Scholar were searched for peer-reviewed articles published from 2000 to 2025. Data from the American Lung Association, CDC, and CDPH were also included. Key words included pediatric asthma, Inland Empire, air pollution, asthma disparity, emergency department utilization, hospitalizations, and socioeconomic status. 

Results 
Asthma has disproportionately affected the IE, consisting of San Bernardino (SB) and Riverside Counties. Geographically, the IE is surrounded by mountains that entrap pollutants such as vehicle emissions and industrial waste, limiting air circulation. Approximately 4 out of the top 5 most polluted cities in North America are located in the IE. Asthma ED visit rate in SB for children 0-17 years old was 60.5% and Riverside 59.3%, while the California average was 56.7%. Hospitalization rates for 0–4-year-olds were 24.4% for SB compared to California’s 17.3%. The elevated rates among school-aged children underscore the crucial need for interventions aimed at improving air quality, enhancing asthma management, and increasing access to preventive healthcare. 

Conclusion 
Pediatric asthma is a pressing matter of concern as it impairs the normal development of children, exerts a long-lasting impact on adolescent learning, disproportionately impacts underserved communities, and places a significant burden on the healthcare system. Here we highlight the unique determinants underlying the high prevalence of asthma in the 0–17-year-old population within the IE/SB, which includes heightened environmental risks (e.g. indoor allergens and air pollutants), socioeconomic barriers, lack of targeted public health initiatives. and unmet need for specialist-oriented care. We also emphasize the need for more research to improve the public health determinants of the IE. Future research should prioritize investigation of region-specific elements to develop tailored clinical strategies that will improve long-term outcomes for vulnerable pediatric patients in the IE.

Pediatric Asthma in Inland Empire: Analysis of Environmental Burden, Gaps in Care, and Unmet Needs

Artificial intelligence (AI) is transforming athletic training, offering novel tools to enhance performance, optimize recovery, and reduce injury risk. This systematic review synthesizes findings from 55 studies evaluating the integration of AI—particularly machine learning (ML) and deep learning (DL)—into sport-specific monitoring systems. These systems incorporate wearable data, video analysis, force measurements, and psychological profiling to support real-time decision-making in training and rehabilitation. Core applications are categorized across two main domains: (1) injury prevention, including movement analysis, fatigue/stimulus monitoring, and recovery forecasting; and (2) advancements to sport, including performance prediction, enhancement, and sport-specific adaptations. Across studies, models such as support vector machines (SVM), convolutional neural networks (CNN), long short-term memory (LSTM), and ensemble methods demonstrated predictive accuracies exceeding 90% in many contexts. This review highlights the potential of AI to augment the precision and scalability of athletic training, while also identifying current limitations, including data standardization, interpretability, and ethical oversight. Recommendations are offered to advance the responsible implementation of AI in athletic training for sport.


Artificial Intelligence in Athletic Training: A Systematic Review of Applications in Injury Prevention and Performance Optimization

Background: Asthma is a chronic lung disease characterized by airway hyperresponsiveness leading to reduction in quality of life. Volatile organic compounds (VOCs), easily evaporable chemicals found in fragrances, cleaning chemicals, and personal care products, are known to exacerbate asthma. The home can be a source of asthma triggers, including VOCs, leading to uncontrolled disease. Minimizing triggers in the home is essential for controlling asthma. Given that women are more likely to have greater severity of asthma than men, it is unknown whether there are gender differences in home VOC exposure. The purpose of this project is to examine any differences in VOC levels in the home by gender and education in older adults with asthma.

Methods: In this secondary analysis of a retrospective observational study, older adults ages 60 and above with asthma had VOC levels measured in their homes over a 24-hour period. Participants also completed baseline metrics of lung function and asthma control including forced expiratory volume (FEV-1), asthma control test (ACT), and Fractional Exhaled Nitric Oxide (FeNO). The 19 specific VOCs included in this analysis were detected indoors in 90% of homes or higher.

Results: Participants (N=184) were primarily White (77%), had a mean age at enrollment of 69±6.2 years, and included a female to male ratio of 2.7:1. Almost half (27.8%) were college educated, however 5.4% had less than a high school education. About one-third (33.7%) had an FEV1 percent predicted ≤79%, 36.4% had FeNO ≥25, and 56% had an ACT ≤19. The average of the total VOCs in each home was 68.36±87.37 parts per billion (ppb), the maximum was 603.69 ppb, minimum was 3.41 ppb, and the interquartile range (IQR) was 55.22 ppb. Acetone had the highest mean, median, and IQR of the 19 VOCs across the homes. Males had significantly higher levels of 124-trimethlybenzene in their homes (p= 0.005). Participants with less than a high school education had significantly higher levels of indoor freon113 and of carbon tetrachloride (p=0.019 and p= 0.013, respectively).

Conclusion: Differences in the concentration of specific VOCs in the homes of older adults with asthma by gender and education were identified. These findings may inform education and intervention strategies to reduce residential VOC exposure and improve asthma control in vulnerable populations.

Gender and education differences in residential levels of volatile organic compounds in older adults with asthma.

### Background
Multi-target peptide therapeutics targeting glucagon receptor (GCGR), glucagon-like peptide-1 receptor (GLP1R), and glucose-dependent insulinotropic polypeptide receptor (GIPR) represent a promising approach for treating diabetes and obesity. Triple agonist peptides demonstrate superior efficacy compared to single-target approaches, yet rational design remains computationally challenging due to complex sequence-structure-activity relationships. Existing methods, primarily based on convolutional neural networks, impose limitations including fixed sequence lengths and inadequate representation of molecular topology. Graph Attention Networks(GAT) offer advantages in capturing molecular structures and variable-length peptide sequences while providing interpretable insights into receptor-specific binding determinants.

### Objective
To develop and validate a GAT-based framework for designing novel triple agonist peptides with optimized binding affinity across GCGR, GLP1R, and GIPR, and to compare performance against convolutional neural network approaches.
Methods: A dataset of 234 peptide sequences with experimentally determined binding affinities was compiled from multiple sources. Peptides were represented as molecular graphs with seven-dimensional node features encoding physicochemical properties and positional information. The GAT architecture employed a shared encoder with task-specific prediction heads, implementing transfer learning to address limited GIPR training data. Performance was evaluated using 5-fold cross-validation and independent validation on 24 literature-derived sequences. A genetic algorithm framework was developed for peptide sequence optimization, incorporating multi-objective fitness evaluation based on predicted binding affinity, biological plausibility, and sequence novelty.

### Results
Cross-validation demonstrated robust GAT performance across all receptors, with GCGR achieving high accuracy (AUC-ROC: 0.915 ± 0.050), followed by GLP1R (AUC-ROC: 0.853 ± 0.059), and GIPR showing acceptable performance despite limited data (AUC-ROC: 0.907 ± 0.083). Comparative analysis revealed receptor-specific advantages: GAT significantly outperformed CNN for GCGR prediction (RMSE: 0.942 vs 1.209, p = 0.0013), while CNN maintained superior GLP1R performance (RMSE: 0.552 vs 0.723). Genetic algorithm optimization achieved substantial improvement over baseline, with 4.0% fitness enhancement and generation of 20 candidates exhibiting mean binding probabilities exceeding 0.5 across all targets.

### Conclusions
The GAT-based framework represents a significant advancement in computational peptide design, demonstrating receptor-specific advantages and robust optimization capabilities. Genetic algorithm optimization enables systematic exploration of sequence space while maintaining biological constraints. This approach provides a rational framework for prioritizing experimental validation efforts in triple agonist development.

Machine Learning-Guided Design of Next-Generation Triple Agonist Peptide Therapeutics for Metabolic Disease

### Background
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a high recurrence and metastatic rate, leading to a 12% survival rate in patients with metastatic TNBC. Chimeric antigen receptor (CAR) T cell therapy represents a promising therapeutic approach, as it involves genetically modifying T cells by introducing genes encoding a synthetic CAR, which is subsequently expressed on the T cell surface. This modification enables CAR T cells to combine the cytolytic activity of T cells with the antigen-specific recognition ability of a single- chain variable fragment (scFv) domain. This study aims to identify potential gene targets for CAR T cell therapy in brain metastases of TNBC (BM TNBC).

### Methods
Matched primary and brain metastatic TNBC tumor samples from three patients were obtained from the KUMC Biospecimen Repository Core Facility. RNA expression profiling was conducted using the GeoMx Digital Spatial Profiler (NanoString Technologies) in the Andrew Godwin Lab at KUMC. Gene expression was analyzed with the GeoMx Human Cancer Transcriptome Atlas (CTA), which quantifies the expression of approximately 1,800 genes. RNA quantification was performed using nCounter and next-generation sequencing (NGS). Differential gene expression was assessed by comparing metastatic tumor samples to a baseline negative control, with genes exhibiting a ≥2-fold increase in expression identified via volcano plots. Statistical significance was determined using one-way ANOVA with multiple comparisons (Prism software, p < 0.05).

### Results
Secreted phosphoprotein 1 (SPP1) was identified as a highly upregulated gene in metastatic tumor samples compared to normal tissue. SPP1 plays a critical role in tumor proliferation, migration, and chemoresistance, making it a promising candidate for targeted CAR T cell therapy. In vitro CAR T cell experiments are ongoing to assess the efficacy of SPP1-targeted therapies in eliminating TNBC cells.

### Conclusion
This study identifies SPP1 as a highly expressed antigen in BM-TNBC, suggesting its potential as a novel target for CAR T cell therapy. Further investigation through functional assays and animal studies will determine its viability as a therapeutic target in this challenging TNBC subtype.

Assessing Expressed Tumor Antigens for TNBC: A GeoMx Analysis

### Background
Robust, inexpensive biomarkers that capture the combined effects of systemic inflammation, tissue hypoperfusion, and nutritional reserve are needed to refine post–acute myocardial infarction (AMI) risk stratification—especially in the large subset that develops congestive heart failure (CHF). Two emerging candidates are the lactate/albumin ratio (LAR) and the red cell distribution width/albumin ratio (RAR). Separate studies have linked each ratio to short and long term mortality in critical illness, AMI, and heart failure, yet no work has directly compared their performance in a contemporary cardiac cohort, nor examined whether percutaneous coronary intervention (PCI) modulates their prognostic value. We addressed this evidence gap in a large, multi hospital dataset.

### Methods
We performed a retrospective secondary analysis of 8 115 de identified encounters drawn from the HCA corporate database (2016 2024). Adults aged 30–80 years with laboratory confirmed AMI complicated by CHF and documented lactate, RDW, and albumin levels were included; those lacking 90 day follow up or requisite labs were excluded. The primary outcome was all cause mortality at 30, 60, and 90 days. Secondary outcomes were 7 , 15 , and 30 day readmissions. Predictors entered into generalized logistic regression were LAR, RAR, age, sex, race, and PCI status; interaction terms tested whether PCI modified biomarker effects. Model discrimination was assessed with the concordance (C) statistic.

### Results
Elevated LAR and elevated RAR each independently increased the odds of death after adjustment for demographics and PCI. For LAR, the odds of mortality were nearly tripled (OR 2.99, 95 % CI 2.62–3.42; p < 0.001). RAR exerted a significant, but comparatively smaller, (OR 1.68, 95 % CI 1.50–1.89; p < 0.001). Age conferred a 3.8 % rise in mortality odds per year. Female sex, non White race, and receipt of PCI were protective (all p < 0.05). The full model achieved moderate discrimination (C = 0.708). Importantly, elevated LAR, but not RAR, predicted early clinical deterioration, being significantly associated with 7 , 15 , and 30 day readmissions. No significant interaction between PCI and either ratio was observed.

### Conclusion


Both LAR and RAR are powerful, readily obtainable predictors of short term mortality in CHF patients recovering from AMI, with LAR also signaling imminent readmission risk. Routine calculation of these ratios at admission could sharpen bedside prognostication and prompt closer surveillance of high risk individuals. Incorporating LAR and RAR into post AMI care pathways warrants prospective validation and may foster a habit of leveraging routinely collected laboratory data for precision cardiovascular medicine.


Lactate/Albumin and RDW/Albumin Ratios for Mortality and Readmission in Post-MI Heart Failure

Currently, there is no national curricular standard for teaching medical students how to respond to an opioid overdose. At VCOM-Virginia, first-year medical students are trained using the Virginia-state naloxone training program (REVIVE!). This program, however, consists only of a lecture-based training with a pre- and post-training assessment. Prior to this study, there has never been a hands-on component or an assessment of long-term retention. This study was designed as a randomized control trial and took place at the VCOM - Virginia Campus’s Simulation Center. Participants include medical students at VCOM-VA who had never received naloxone training. We enrolled 255 participants, with 96 comprising the control group (w/o simulation) and 114 in the experimental (w/ simulation) after losing participants to follow up. IRB approval was received on 9/26/23 (VCOM IRB Record # 2023-132). The intervention offered to the control group was the unaltered Virginia REVIVE! course curriculum. The experimental group received the classroom-based curriculum, alongside a simulation experience utilizing a high-fidelity manikin synced to the Laerdal Learning Application software. Participants were tasked with assessing the manikin’s vital signs, deciding if their case was severe alcohol intoxication or opioid overdose, and following the rescue protocol as outlined in the didactic portion. All participants received the same 2 post-assessment surveys based on the learning objectives outlined in the REVIVE! course, one immediately following the didactic portion, and one at 6 months following their training date. Additionally, time to recognize a situation as an overdose and self-reported confidence scores were recorded from students following their simulation. At 6-month follow-up, there was a significant difference in average time to recognition between the simulation-trained group and control group. There was also a statistically significant difference in confidence in real world performance with a higher confidence seen in the simulation trained group. Additionally, the simulation-trained group had a smaller difference in post-assessment score change at the 6 month mark; however these results were not statistically significant, thus we can make no conclusions about long-term material retention at this time. Results of this study show that medical students who receive simulation training in opioid overdose rescue feel more confident and respond more quickly than those who receive traditional classroom-based training. In the larger context of medical education, these findings highlight the potential for simulation-based learning to enhance student preparedness and confidence in critical hands-on skills such as naloxone administration. A high-fidelity manikin approach could also be extended to other clinical skills, reinforcing the philosophy of patient-focused care through innovative teaching methods.

Hands-On Naloxone Training: Advancing Curriculum and Assessment Through Simulated Manikins Learning

### Background
Esophageal squamous cell carcinoma (ESCC) disproportionately affects Asian populations and frequently arises in the upper esophagus. Although racial differences in ESCC incidence are recognized, real-world evidence comparing metastatic burden and survival outcomes between Asian and White patients remains scarce. Even less is known about whether these disparities differ by sex. This study evaluates racial disparities in metastasis and 5-year survival among patients with upper esophageal cancer, with novel stratification by sex.

### Methods
We performed a retrospective cohort study using the TriNetX Research Network. Adults (≥18 years) with upper esophageal cancer were identified by ICD-10-CM and ICD-O codes with exclusion of many other cancers. Asian and White patients were propensity score matched 1:1 on age, sex, ethnicity, and nicotine use, then stratified by sex. Metastasis was defined as secondary malignancies to high-yield organs documented after the index upper esophageal cancer diagnosis. Survival was analyzed with Kaplan–Meier methods. Hazard ratios (HR), risk ratios (RR), odds ratios (OR), and 95% confidence intervals (CI) were calculated.

### Results
The matched cohort included 2,268 Asian and 2,268 White patients. Metastasis occurred more frequently in Asian patients (53.0% vs. 29.0%; RR 1.84, OR 2.80, p < 0.0001). Five-year survival was significantly lower in Asian patients (27.6% vs. 41.6%; HR 1.42, p < 0.0001). Among males, metastasis was 54.4% in Asian males vs. 29.9% in White males (p < 0.0001), with 5-year survival of 26.0% in Asian males vs. 38.8% in White males (p < 0.0001). Among females, metastasis remained higher in Asian females (33.9% vs. 18.3%; p < 0.0001), but survival differences were not statistically significant (35.9% vs. 40.5%; p = 0.33).

### Conclusions
Asian patients with upper esophageal cancer, regardless of sex, experience greater metastatic burden compared to their White counterparts. Regarding differences in 5-year survival, Asian patients overall have a decreased survival compared to White patients, mainly attributable to the discrepancies between the male cohorts, with minimal significance in the female cohorts. These disparities may reflect a combination of biological predisposition, decreased health-seeking behaviors, and systemic barriers to care. To address these inequities, culturally tailored screening, early detection, and intervention strategies are urgently needed in high-risk populations, especially in Asian men.

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Dignity in Death: Evaluating a Unique End of Life Care Model that Bridges Hospice and Homelessness

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