Publications by authors named "Maria R H Castro"

3 Publications

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Lessons From Learners: Adapting Medical Student Education During and Post-COVID-19.

Acad Med 2021 May 4. Epub 2021 May 4.

M.R.H. Castro is a third-year medical student, University of California San Francisco School of Medicine, San Francisco, California; ORCID: https://orcid.org/0000-0002-2085-4893. L.M. Calthorpe is a third-year medical student, University of California San Francisco School of Medicine, San Francisco, California; ORCID: https://orcid.org/0000-0002-0496-9471. S.E. Fogh is associate professor, Department of Radiation Oncology, University of California San Francisco School of Medicine, San Francisco, California. S. McAllister is a third-year medical student, University of California San Francisco School of Medicine, San Francisco, California. C.L Johnson is a third-year medical student, University of California San Francisco School of Medicine, San Francisco, California. E.D. Isaacs is professor of emergency medicine, Department of Emergency Medicine, University of California San Francisco, San Francisco, California. A. Ishizaki is manager, Clinical Microsystems Clerkship, University of California San Francisco School of Medicine, San Francisco, California. A. Kozas is curriculum coordinator, Clinical Microsystems Clerkship, University of California San Francisco School of Medicine, San Francisco, California. D. Lo is assistant professor of medicine, Division of Geriatrics, Department of Medicine, University of California San Francisco School of Medicine; and Department of Geriatrics and Extended Care, San Francisco Veterans Affairs Health Care System, San Francisco, California. S. Rennke is professor of medicine, Division of Hospital Medicine, Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California. J. Davis is professor of medicine and associate dean for curriculum, University of California San Francisco School of Medicine, San Francisco, California. A. Chang is professor of medicine, Division of Geriatrics, Department of Medicine, University of California San Francisco, San Francisco, California.

In response to the COVID-19 pandemic, many medical schools suspended clinical clerkships and implemented newly adapted curricula to facilitate continued educational progress. While the implementation of these new curricula has been described, an understanding of the impact on student learning outcomes is lacking. In 2020, the authors followed Kern's 6-step approach to curricular development to create and evaluate a novel COVID-19 curriculum for medical students at the University of California San Francisco School of Medicine and evaluate its learning outcomes. The primary goal of the curriculum was to provide third- and fourth-year medical students an opportunity for workplace learning in the absence of clinical clerkships, specifically for students to develop clerkship-level milestones in the competency domains of practice-based learning and improvement, professionalism, and systems-based practice. The curriculum was designed to match students with faculty-mentored projects occurring primarily in virtual formats. A total of 126 students enrolled in the curriculum and completed a survey about their learning outcomes (100% response rate). Of 35 possible clerkship-level milestones, there were 12 milestones for which over half of students reported development, in competency domains including practice-based learning and improvement, professionalism, and interpersonal and communication skills. Thematic analysis of students' qualitative survey responses demonstrated 2 central motivations for participating in the curriculum: identity as physicians-in-training, and patient engagement. Six central learning areas were developed during the curriculum: interprofessional teamwork, community resources, technology in medicine, skill-building, quality improvement, and specialty-specific learning. This analysis demonstrates that students can develop competencies and achieve rich workplace learning through project-based experiential learning, even in virtual clinical workplaces. Furthermore, knowledge of community resources, technology in medicine, and quality improvement were developed through the curriculum more readily than in traditional clerkships, and could be considered as integral learning objectives in future curricular design.
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http://dx.doi.org/10.1097/ACM.0000000000004148DOI Listing
May 2021

DNA methylation profiling demonstrates superior diagnostic classification to RNA-sequencing in a case of metastatic meningioma.

Acta Neuropathol Commun 2020 06 9;8(1):82. Epub 2020 Jun 9.

Department of Radiation Oncology, University of California San Francisco, California, 94143, USA.

Meningiomas are the most common primary intracranial tumors, but meningioma metastases are rare. Accordingly, the clinical workup, diagnostic testing, and molecular classification of metastatic meningioma is incompletely understood. Here, we present a case report of multiply recurrent meningioma complicated by liver metastasis. We discuss the patient presentation, imaging findings, and conventional histopathologic characterization of both the intracranial lesion and the metastatic focus. Further, we perform multiplatform molecular profiling, comprised of DNA methylation arrays and RNA-sequencing, of six stereotactically-guided samples from the intracranial meningioma and a single ultrasound-guided liver metastasis biopsy. Our results show that DNA methylation clusters distinguish the liver metastasis from the intracranial meningioma samples, and identify a small focus of hepatocyte contamination with the liver biopsy. Nonetheless, DNA methylation-based classification accurately identifies the liver metastasis as a meningioma with high confidence. We also find that clustering of RNA-sequencing results distinguishes the liver metastasis from the intracranial meningiomas samples, but that differential gene expression classification is confounded by hepatocyte-specific gene expression programs in the liver metastasis. In sum, this case report sheds light on the comparative biology of intracranial and metastatic meningioma. Furthermore, our results support methylation-based classification as a robust method of diagnosing metastatic lesions, underscore the broad utility of DNA methylation array profiling in diagnostic pathology, and caution against the routine use of bulk RNA-sequencing for identifying tumor signatures in heterogeneous metastatic lesions.
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http://dx.doi.org/10.1186/s40478-020-00952-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7285578PMC
June 2020

More than myelin: Probing white matter differences in prematurity with quantitative T1 and diffusion MRI.

Neuroimage Clin 2019 12;22:101756. Epub 2019 Mar 12.

Division of Developmental and Behavioral Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA. Electronic address:

Objective: We combined diffusion MRI (dMRI) with quantitative T1 (qT1) relaxometry in a sample of school-aged children born preterm and full term to determine whether reduced fractional anisotropy (FA) within the corpus callosum of the preterm group could be explained by a reduction in myelin content, as indexed by R1 (1/T1) from qT1 scans.

Methods: 8-year-old children born preterm (n = 29; GA 22-32 weeks) and full term (n = 24) underwent dMRI and qT1 scans. Four subdivisions of the corpus callosum were segmented in individual native space according to cortical projection zones (occipital, temporal, motor and anterior-frontal). Fractional anisotropy (FA) and R1 were quantified along the tract trajectory of each subdivision and compared across two birth groups.

Results: Compared to controls, preterm children demonstrated significantly decreased FA in 3 of 4 analyzed corpus callosum subdivisions (temporal, motor, and anterior frontal segments) and decreased R1 in only 2 of 4 corpus callosum subdivisions (temporal and motor segments). FA and RD were significantly associated with R1 within temporal but not anterior frontal subdivisions of the corpus callosum in the term group; RD correlated with R1 in the anterior subdivision in the preterm group only.

Conclusions: Myelin content, as indexed by R1, drives some but not all of the differences in white matter between preterm and term born children. Other factors, such as axonal diameter and directional coherence, likely contributed to FA differences in the anterior frontal segment of the corpus callosum that were not well explained by R1.
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http://dx.doi.org/10.1016/j.nicl.2019.101756DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428958PMC
January 2020