Aaron M Rosado, MD PhD

Aaron M Rosado, MD PhD

Emory & Henry College

H-index: 3

North America-United States

About Aaron M Rosado, MD PhD

Aaron M Rosado, MD PhD, With an exceptional h-index of 3 and a recent h-index of 2 (since 2020), a distinguished researcher at Emory & Henry College, specializes in the field of Immunology, co-stimulation, biomechanics, biophysics, biomedical engineering.

His recent articles reflect a diverse array of research interests and contributions to the field:

Memory in repetitive protein–protein interaction series

CD28 and TCR In-Situ Biophysical Analyses Inform T Cell Immunity Mechanisms

Localized hydrogel delivery of dendritic cells for attenuation of multiple sclerosis in a murine model

Machine learning algorithm for early mortality prediction in patients with advanced penile cancer

Aaron M Rosado, MD PhD Information

University

Emory & Henry College

Position

MSTP Student

Citations(all)

62

Citations(since 2020)

59

Cited By

25

hIndex(all)

3

hIndex(since 2020)

2

i10Index(all)

2

i10Index(since 2020)

2

Email

University Profile Page

Emory & Henry College

Aaron M Rosado, MD PhD Skills & Research Interests

Immunology

co-stimulation

biomechanics

biophysics

biomedical engineering

Top articles of Aaron M Rosado, MD PhD

Memory in repetitive protein–protein interaction series

Authors

Aaron M Rosado,Yan Zhang,Hyun-Kyu Choi,Yunfeng Chen,Samuel M Ehrlich,Fengzhi Jin,Arash Grakoui,Brian D Evavold,Cheng Zhu

Journal

APL Bioengineering

Published Date

2023/3/1

Interactions between proteins coordinate biological processes in an organism and may impact its responses to changing environments and diseases through feedback systems. Feedback systems function by using changes in the past to influence behaviors in the future, which we refer to here as memory. Here, we summarized several observations made, ideas conceptualized, and mathematical models developed for quantitatively analyzing memory effects in repetitive protein–protein interactions (PPIs). Specifically, we consider how proteins on the cell or in isolation retain information about prior interactions to impact current interactions. The micropipette, biomembrane force probe, and atomic force microscopic techniques were used to repeatedly assay PPIs. The resulting time series were analyzed by a previous and two new models to extract three memory indices of short (seconds), intermediate (minutes), and …

CD28 and TCR In-Situ Biophysical Analyses Inform T Cell Immunity Mechanisms

Authors

Aaron Michael Rosado

Published Date

2021/11/1

Among contexts critically shaping immune responses include T cell development (19), activation (258), and differentiation (259). T cells originate from thymocytes in the thymus that undergo selection to ensure reactive T cells without autoreactivity. T cells emerging from the thymus fall into two major groups based on whether their developed TCR recognize MHC class I or class II molecule presented peptides. After thymic development, the TCR enables T cells to recognize antigens and antigen recognition drives T cell mediated immunity (19). CD28 signalling profoundly influences T cell immunity, but

Localized hydrogel delivery of dendritic cells for attenuation of multiple sclerosis in a murine model

Authors

Aline M Thomas,Nicholas M Beskid,Jennifer L Blanchfield,Aaron M Rosado,Andrés J García,Brian D Evavold,Julia E Babensee

Journal

Journal of Biomedical Materials Research Part A

Published Date

2021/7

In multiple sclerosis (MS), abnormally activated immune cells responsive to myelin proteins result in widespread damage throughout the central nervous system (CNS) and ultimately irreversible disability. Immunomodulation by delivering dendritic cells (DCs) utilizes a potent and rapid MS disease progression driver therapeutically. Here, we investigated delivering DCs for disease severity attenuation using an experimental autoimmune encephalomyelitis preclinical MS model. DCs treated with interleukin‐10 (IL‐10) (DC10s) were transplanted using in situ gelling poly(ethylene glycol)‐based hydrogel for target site localization. DC delivery increased hydrogel longevity and altered the injection site recruited, endogenous immune cell profile within 2 days postinjection. Furthermore, hydrogel‐mediated DC transplantation efficacy depended on the injection‐site. DCs delivered to the neck local to MS‐associated CNS …

Machine learning algorithm for early mortality prediction in patients with advanced penile cancer

Authors

Robert Chen,Matthew R Kudelka,Aaron M Rosado,James Zhang

Journal

medRxiv

Published Date

2020/4/25

Penile cancer remains a rare cancer with an annual incidence of 1 in 100,000 men in the United States, accounting for 0.4-0.6% of all malignancies. Furthermore, to date there are no predictive models of early mortality in penile cancer. Meanwhile, machine learning has potential to serve as a prognostic tool for patients with advanced disease.We developed a machine learning model for predicting early mortality in penile cancer (survival less than 11 months after initial diagnosis. A cohort of 88 patients with advanced penile cancer was extracted from the Surveillance, Epidemiology and End Results (SEER) program. In the cohort, patients with advanced penile cancer exhibited a median overall survival of 21 months, with the 25th percentile of overall survival being 11 months. We constructed predictive features based on patient demographics, staging, metastasis, lymph node biopsy criteria, and metastatic sites. We trained a multivariate logistic regression model, tuning parameters with respect to regularization, and feature selection criteria.Upon evaluation with 5-fold cross validation, our model achieved 68.2% accuracy with AUC 0.696. Criteria for advanced staging (T4, group stage IV), as well as higher age, white race and squamous cell histology, were the most predictive of early mortality. Tumor size was the strongest negative predictor of early mortality.Our study showcases the first known predictive model for early mortality in patients with advanced penile cancer and should serve as a framework for approaching the clinical problem in future studies. Future work should aim to incorporate other data sources such as genomic and metabolomic …

See List of Professors in Aaron M Rosado, MD PhD University(Emory & Henry College)

Aaron M Rosado, MD PhD FAQs

What is Aaron M Rosado, MD PhD's h-index at Emory & Henry College?

The h-index of Aaron M Rosado, MD PhD has been 2 since 2020 and 3 in total.

What are Aaron M Rosado, MD PhD's top articles?

The articles with the titles of

Memory in repetitive protein–protein interaction series

CD28 and TCR In-Situ Biophysical Analyses Inform T Cell Immunity Mechanisms

Localized hydrogel delivery of dendritic cells for attenuation of multiple sclerosis in a murine model

Machine learning algorithm for early mortality prediction in patients with advanced penile cancer

are the top articles of Aaron M Rosado, MD PhD at Emory & Henry College.

What are Aaron M Rosado, MD PhD's research interests?

The research interests of Aaron M Rosado, MD PhD are: Immunology, co-stimulation, biomechanics, biophysics, biomedical engineering

What is Aaron M Rosado, MD PhD's total number of citations?

Aaron M Rosado, MD PhD has 62 citations in total.

What are the co-authors of Aaron M Rosado, MD PhD?

The co-authors of Aaron M Rosado, MD PhD are Aline Thomas.

    Co-Authors

    H-index: 13
    Aline Thomas

    Aline Thomas

    Johns Hopkins University

    academic-engine

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