Medicine and Health Sciences Commons^™

Advancing Risk Stratification In Hfpef: Unveiling The Potential Of Cardiac Fibrosis Markers For Early Diagnosis And Enhanced Patient Outcomes, Mariam Abdeen

Rowan-Virtua Research Day

Heart failure with preserved ejection fraction (HFpEF) challenges clinicians due to its diverse presentation and limitations in traditional diagnostic criteria. This study delves into the potential of cardiac fibrosis markers like galectin-3, NT-proBNP, and trimethylamine N-oxide (TMAO) to enhance diagnostic precision and patient outcomes in HFpEF. A systematic review of sixteen relevant studies revealed that these biomarkers offer promise for early detection and improved risk assessment. For instance, TMAO indicates systemic implications of HFpEF, while galectin-3 shows predictive value across heart failure types. Additionally, machine-learning models incorporating multiple biomarkers predict significant risk of adverse outcomes. Despite these advances, challenges like …

Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang

Rowan-Virtua Research Day

The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the …

Correlation Between Gut Biomarkers And Depression, Jianle Gao

Rowan-Virtua Research Day

The correlation between the gut-microbiota- brain axis and mental state in the context of mental disorders such as Major Depressive Disorder (MDD), Schizophrenia, etc. has been well studied. Production of inflammatory and non-inflammatory metabolites by the gut- microbiota directly and indirectly affects the brain and mood. Therefore, colonization by maladaptive, pro-inflammatory bacteria may cause mood dysregulation and depressive features. Metabolites from these bacteria can be quantitatively analyzed for use as biomarkers of Major Depressive Disorder. Biomarkers studied include: serotonin, dopamine, butyrate, acetate, and propionate.

Inflammatory Marker Levels Among Patients Diagnosed With Autism Spectrum Disorder And Congenital Heart Defects, Patrick Pearce, Venkateswar Venkataraman, Andrea Iannuzzelli, Jennifer Lecomte

Rowan-Virtua Research Day

Autism Spectrum Disorder (ASD) and congenital heart defects (CHD) are conditions that both confer an immense increase in standard of care, and utilization of medical resources addressing comorbidities. One shared symptom that has been consistently cited is inflammation. This review sought to explore the levels of Tumor Necrosis Factor-𝞪 (TNF-𝞪) and Interleukin-6 (IL-6) between patients diagnosed as having either ASD or CHD. By compiling published data containing the mean values of these two inflammatory markers within these populations, it was shown that while both have significantly elevated levels compared to a phenotypically normal demographic, there is no significant difference between …

Associations Of Maternal Plasma Free Fatty Acid Profiles With Markers Of Inflammation In Healthy Pregnant Women, Xinhua Chen Md, Thomas P. Stein Phd, Theresa O. Scholl Phd, Robert A. Steer Edd

Rowan-Virtua Research Day

We investigated the relationship between maternal fasting plasma free fatty acid (FFA) profiles and markers of inflammation (MOI) (IL-6, 8, 10, TNF-α, granulocyte macrophage colony-stimulating factor (GMCSF) and resistin) in healthy pregnant women during early gestation (week 16).

These data suggested that maternal functional long-chain FFAs influence inflammatory response during normal pregnancy. Changes in specific FFA composition may reduce low-grade inflammation and inflammation related poor pregnancy outcomes and complications.