Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Amino Acids, Peptides, and Proteins (2)
- Life Sciences (2)
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Animal Experimentation and Research (1)
- Bioimaging and Biomedical Optics (1)
-
- Biomedical (1)
- Biomedical Engineering and Bioengineering (1)
- Cancer Biology (1)
- Cell and Developmental Biology (1)
- Diagnosis (1)
- Diseases (1)
- Electrical and Computer Engineering (1)
- Engineering (1)
- Hormones, Hormone Substitutes, and Hormone Antagonists (1)
- Medical Specialties (1)
- Research Methods in Life Sciences (1)
- Urology (1)
Articles 1 - 3 of 3
Full-Text Articles in Chemicals and Drugs
Differential Tissue Response To Growth Hormone In Mice, Ryan Berry, Graham R. Mcginnis, Ronadip R. Banerjee, Martin E. Young, Stuart J. Frank
Differential Tissue Response To Growth Hormone In Mice, Ryan Berry, Graham R. Mcginnis, Ronadip R. Banerjee, Martin E. Young, Stuart J. Frank
Kinesiology and Nutrition Sciences Faculty Publications
Growth hormone (GH) has been shown to act directly on multiple tissues throughout the body. Historically, it was believed that GH acted directly in the liver and only indirectly in other tissues via insulin‐like growth hormone 1 (IGF‐1). Despite extensive work to describe GH action in individual tissues, a comparative analysis of acute GH signaling in key metabolic tissues has not been performed. Herein, we address this knowledge gap. Acute tissue response to human recombinant GH was assessed in mice by measuring signaling via phospho‐STAT5 immunoblotting. STAT5 activation is an easily and reliably detected early marker of GH receptor engagement. …
Adjacent Slice Prostate Cancer Prediction To Inform Maldi Imaging Biomarker Analysis, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Adjacent Slice Prostate Cancer Prediction To Inform Maldi Imaging Biomarker Analysis, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Electrical & Computer Engineering Faculty Publications
Prostate cancer is the second most common type of cancer among men in US [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from the …
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …