Scott Rodriguez

ORCID: 0000-0001-6061-0837
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About
Contact & Profiles
Research Areas
  • Radiomics and Machine Learning in Medical Imaging
  • Glioma Diagnosis and Treatment
  • MRI in cancer diagnosis
  • Cancer Genomics and Diagnostics
  • Transboundary Water Resource Management
  • Diabetes Treatment and Management
  • Advanced Electron Microscopy Techniques and Applications
  • Neuropeptides and Animal Physiology
  • Peptidase Inhibition and Analysis
  • International Environmental Law and Policies
  • Environmental law and policy

Texas A&M University School of Law
2017

Stanford University
2015-2016

Stanford Medicine
2016

University of California, Santa Cruz
2016

Saint Mary's College of California
2008

Quantitative imaging stratifies glioblastoma into three different phenotypes with distinct molecular activities independent of established markers and clinical status.

10.1126/scitranslmed.aaa7582 article EN Science Translational Medicine 2015-09-02

In previous clinical trials, antiangiogenic therapies such as bevacizumab did not show efficacy in patients with newly diagnosed glioblastoma (GBM). This may be a result of the heterogeneity GBM, which has variety imaging-based phenotypes and gene expression patterns. this study, we sought to identify phenotypic subtype GBM who have distinct tumor-image features molecular activities benefit from therapies.Quantitative image characterizing subregions tumors whole tumor were extracted...

10.1093/neuonc/now270 article EN Neuro-Oncology 2016-12-22

<h3>BACKGROUND AND PURPOSE:</h3> Tumor location has been shown to be a significant prognostic factor in patients with glioblastoma. The purpose of this study was characterize glioblastoma lesions by identifying MR imaging voxel-based tumor features that are associated molecular profiles, patient characteristics, and clinical outcomes. <h3>MATERIALS METHODS:</h3> Preoperative T1 anatomic images 384 glioblastomas were obtained from 2 independent cohorts (<i>n</i> = 253 the Stanford University...

10.3174/ajnr.a4631 article EN cc-by American Journal of Neuroradiology 2016-01-07

Thimet oligopeptidase (EC 3.4.24.15) is a zinc(II) endopeptidase implicated in the processing of numerous physiological peptides. Although its role selecting and peptides not fully understood, it believed that flexible loop regions lining substrate‐binding site allow enzyme to conform substrates varying structure. This study describes mutant forms thimet which Gly or Tyr residues 599–611 region were replaced, individually combination, elucidate mechanism substrate selection by this enzyme....

10.1111/j.1742-4658.2008.06685.x article EN FEBS Journal 2008-10-09

INTRODUCTION: Glioblastoma is the most common and aggressive primary human brain cancer. Noninvasive characterization of intratumor blood flow parameters may help guide clinical decision making. Beyond risk stratification prognostication, tumor perfusion inform treatment selection serial monitoring newer antiangiogenic targeted therapies. In this study, intra- intertumor variations in volume were quantified by using a novel 3-D volumetric, dynamic-susceptibility contrast-enhanced (DSCE),...

10.1227/01.neu.0000467085.78226.37 article EN Neurosurgery 2015-07-17
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