About

Taylor Brown is an assistant professor of statistics at the University of Virginia. His research interests focus on state space models, particle filtering, and Markov chain Monte Carlo algorithms. He specializes in Bayesian statistics, computational statistics, and time series analysis. Brown earned his PhD in Statistics from the University of Virginia in 2018, following an MS in Statistics and a BA in Mathematics and Economics from the University of Connecticut. His work addresses challenges in real-time Bayesian forecasting, particularly with posterior predictive distributions for time series data, and he has contributed to the development of computational methods such as particle swarm algorithms and pseudo-marginal samplers. Brown also teaches a variety of advanced statistics courses, including Bayesian machine learning, advanced inference, and applied time series, reflecting his expertise in both theoretical and applied aspects of statistical science.

Research topics

• Medicine
• Surgery
• Cardiology
• Internal medicine

Selected publications

• Advancing treatment of spinal muscular atrophy through inhibition of the myostatin signaling pathway

  Expert Review of Neurotherapeutics · 2026-01-22

  article

  INTRODUCTION: In spinal muscular atrophy (SMA), irreversible loss of spinal motor neurons and progressive skeletal muscle atrophy cause continuous weakness and loss of motor function. Treatments that increase levels of survival motor neuron (SMN) protein in motor neurons have greatly improved prognoses for patients, but significant unmet needs remain. Myostatin is a protein secreted by skeletal muscle that acts as a negative regulator of muscle growth. Inhibition of the myostatin signaling pathway may improve motor function in SMA and other neuromuscular diseases. AREAS COVERED: This article reviews the role of muscle in SMA and the potential for treatments that inhibit the myostatin signaling pathway in neuromuscular diseases. Preclinical and clinical trial data are discussed for these muscle-targeted treatments in development for SMA. EXPERT OPINION: SMN-targeted disease-modifying treatments focus on motor neuron survival rather than muscle. Treated individuals nonetheless experience a range of persistent muscle weakness. Treatments that inhibit myostatin signaling represent a potential complementary pathway for direct muscle enhancement. In the evolving SMA treatment landscape, understanding how muscle-targeted treatment can be incorporated into clinical practice will facilitate individualized treatment decisions and identify outcomes that best encapsulate maintenance or improvement of motor function across the phenotypic spectrum of SMA.

  PublisherDOI

• Normothermic Regional Perfusion: Why Isn't the Lactate Coming Down?

  Clinical Transplantation · 2026-03-01

  article

  ABSTRACT During normothermic regional perfusion (NRP), lactate is the most commonly used liver viability marker. Lactate production from pyruvate breakdown in erythrocytes is not suspended during pRBC storage. By transfusing blood at a variety of stored ages, variable amounts of lactate are added to the NRP circuit and may influence serial lactate measurements. Sixteen DCD donors undergoing NRP were enrolled in a prospective study. Samples were drawn from pRBC bags prior to use in the NRP circuit and were tested for lactate values. Lactate values of the NRP circuit perfusate were also assessed Q15 min. Lactate values of the pRBCs varied from 4.4 mmol/L to >20 mmol/L and were strongly correlated with the age of the stored blood ( r 2 = 0.74). Donors in which the pRBCs were > = 20‐days from expiration (Newer Blood group) had a significantly lower lactate at 60 min of NRP compared to donors in which pRBCs were <20 day from expiration (Older Blood group) (4.0±2.0 mg/dL vs. 6.3±2.3 mg/dL; p = 0.048). If the lactate is not decreasing as anticipated, transfusion of older pRBC should be entertained as one possible explanation. In cases where the liver seems acceptable for transplantation, additional lactate testing with longer time on NRP or sequential NRP/NMP should be considered in lieu of declining the liver outright.

  PublisherDOI

• Persisting Psychosocial Impairments in Adults Being Treated with Medication for Attention Deficit/Hyperactivity Disorder

  Psychopharmacology Bulletin · 2025-08-12 · 12 citations

  article1st authorCorresponding

  Attention-deficit/hyperactivity disorder (ADHD) is a common neurobehavioral condition in childhood.1 Of the 3–10% of children diagnosed with ADHD, it is thought that approximately one- to two-thirds (1–6% of the general population) will continue to have ADHD symptoms in adult life.1 • According to the American Psychiatric Association’s Diagnostic and Statistical Manual, fifth edition (DSM-5), ADHD is characterized by a persistent pattern of inattention, hyperactivity, and impulsivity that interferes with functioning or development.2 • In general, adults diagnosed with ADHD have been shown to have more impairments related to their work/school and social lives than matched samples of adults without ADHD.3–8 These impairments are key components of the diagnosis of ADHD, according to the DSM-5.2 Symptoms necessary for this diagnosis include impairments in interpersonal communication, irritability/mood lability, and cognition (including attention, executive function, or memory).2 • Various scales and instruments, such as the Behavior Rating Inventory of Executive Function-Adult version (BRIEF-A) assessments or the Brown Attention-Deficit Disorder Scale (BADDS), have also been used to assess the impairments in functioning commonly associated with ADHD.9–11

  PublisherDOI

• Unmet Medication Coverage Needs among Adults with Attention Deficit/Hyperactivity Disorder (ADHD)

  Psychopharmacology Bulletin · 2025-08-12 · 2 citations

  article1st authorCorresponding

  Attention-deficit/hyperactivity disorder (ADHD) is a common neurobehavioral condition in childhood that often persists into adulthood.1 Psychostimulant medication has demonstrated efficacy for managing ADHD symptoms in adults.2,3 • The development of formulations with varying durations of effect has greatly expanded the available treatment options for individuals with ADHD.4 Management of ADHD symptoms in adults may involve treatment with either short-acting (SA) medication, long-acting (LA) medication, or an adjunctive LA + SA (AU) medication regimen. These different formulation dosing regimens provide differing durations of effect and thus differing coverage of symptoms that can impair adult patients in their social, work, school, and/or family settings across the entire day (in early morning, late afternoon, and into the evening). • Few studies, however, have investigated how LA/SA formulations and differing formulation dosing regimens relate to differing medication coverage resulting in symptom impairments in adult patients with ADHD.5,6.

  PublisherDOI

• Engineering 101: Peer Teaching with LEGO NXT Robotics

  2025-02-27

  articleOpen access
  PublisherOA PDFDOI

• Remaining Burden of Spinal Muscular Atrophy Among Treated Patients: A Survey of Patients and Caregivers

  Annals of Clinical and Translational Neurology · 2025-07-06 · 2 citations

  articleOpen access

  OBJECTIVE: Spinal muscular atrophy (SMA) significantly impacts motor function. This study aimed to assess the persistent burden and unmet needs among currently treated patients with SMA and their caregivers. METHODS: Two complementary web-based surveys were distributed in August 2024 among patients with SMA and their caregivers. Non-ambulant patients with SMA currently receiving risdiplam or nusinersen, and/or their primary, informal caregivers were eligible to participate. Survey modules captured clinical, humanistic, productivity, and caregiver-related burden of disease. The PROMIS Fatigue and EQ-5D-5L were used to assess fatigue and quality of life. RESULTS: 40 pediatric (mean age 8.3 years; represented by caregiver proxies) and 68 adult patients (mean age 37.5 years) were included, of which the majority were on SMN-targeted treatment for ≥ 2 years (82.5% and 94.1%, respectively), and nearly half were on treatment for ≥ 4 years. Despite continued treatment, muscle weakness was reported in 95% of pediatric and 100% of adult patients, with 63% of pediatric and 68% of adult patients reporting "severe" or "very severe" muscle weakness that substantially impacted motor function and performance of activities of daily living. Increased fatigue and muscle weakness were associated with worse overall health. Findings also demonstrated impacts of SMA on patient quality of life and well-being. Most participants reported mobility limitations and muscle weakness as being least improved by current treatment. INTERPRETATION: Despite the use of current treatments, there remains a significant burden of SMA on patients and their caregivers. Muscle weakness and mobility limitations remain key areas of unmet need.

  PublisherOA PDFDOI

• Structural and Photophysical Investigations of a Novel Copper(I) Photosensitizer Candidate

  SSRN Electronic Journal · 2023-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• DICOM converted whole slide hematoxylin and eosin images of rhabdomyosarcoma from Children's Oncology Group trials

  Zenodo (CERN European Organization for Nuclear Research) · 2023-08-23

  datasetOpen access

  Rhabdomyosarcoma (RMS) is an aggressive soft-tissue sarcoma, which primarily occurs in children and young adults. This dataset contains manifests referring to the hematoxylin and eosin (H&E) stained images in Digital Imaging and Communications in Medicine (DICOM) format available from National Cancer Institute Imaging Data Commons (IDC) [1] (also see IDC Portal at https://imaging.datacommons.cancer.gov) as of data release v16. The original images in vendor-specific format were collected on IRB-approved clinical trials or tissue banking studies from Children’s Oncology Group (COG) patients enrolled on ARST0331, ARST0431, D9602, D9803, and D9902 trials, as described in [2]. Those images, augmented with the metadata describing their content, were provided to the IDC team for the purposes of archival, and were converted into DICOM Whole Slide Microscopy (SM) representation [3], [4] using custom open source scripts and tools available and described here [5]. The resulting converted images were released in IDC in the RMS-Mutation-Prediction collection with the data release v16. To conveniently explore the data available for this dataset, please use this dashboard: https://lookerstudio.google.com/reporting/7f267400-8774-42e1-b5d1-ca11863c52a9. Notebooks demonstrating how to use this data are available here: https://github.com/ImagingDataCommons/IDC-Tutorials/tree/master/notebooks/collections_demos/rms_mutation_prediction. Clinical data accompanying the images is available via SQL interface in IDC BigQuery tables, see details on accessing IDC clinical data in the respective tutorial (https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/clinical_data_intro.ipynb). The images referred to by the accompanying manifests can be explored and visualized using IDC Portal here: https://portal.imaging.datacommons.cancer.gov/explore/. Direct link to open the collection is https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=rms_mutation_prediction. The GCP and AWS manifests provided with this dataset record can be used to download the corresponding files from the IDC Google Cloud Storage (GCS) or Amazon S3 (AWS) buckets free of charge following the instructions available in IDC documentation here: https://learn.canceridc.dev/data/downloading-data. Specifically, you will need to install the s5cmd command line tool on your computer (see instructions at https://github.com/peak/s5cmd#installation), and follow the manifest-specific download instructions accompanying the file list below. If you use the files referenced in the attached manifests, we ask you to please cite this dataset, as well as the publication describing the original dataset [2] and the publication acknowledging IDC [1]. Specific files included in the record are: rms_mutation_prediction_gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: s5cmd --no-sign-request --endpoint-url https://storage.googleapis.com run rms_mutation_prediction_gcs.s5cmd) rms_mutation_prediction_aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: s5cmd --no-sign-request --endpoint-url https://s3.amazonaws.com run rms_mutation_prediction_aws.s5cmd) rms_mutation_prediction_dcf.csv: Gen3-based manifest (see details in https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids). References [1] A. Fedorov et al., "NCI Imaging Data Commons," Cancer Res., vol. 81, no. 16, pp. 4188–4193, Aug. 2021, doi: 10.1158/0008-5472.CAN-21-0950. [2] D. Milewski et al., "Predicting molecular subtype and survival of rhabdomyosarcoma patients using deep learning of H&E images: A report from the Children's Oncology Group," Clin. Cancer Res., vol. 29, no. 2, pp. 364–378, Jan. 2023, doi: 10.1158/1078-0432.CCR-22-1663. [3] National Electrical Manufacturers Association (NEMA), "DICOM PS3.3 - Information Object Definitions: A.32.8 VL Whole Slide Microscopy Image IOD." Accessed: Aug. 11, 2023. [Online]. Available: https://dicom.nema.org/medical/dicom/current/output/html/part03.html#sect_A.32.8 [4] M. D. Herrmann et al., "Implementing the DICOM standard for digital pathology," J. Pathol. Inform., vol. 9, no. 1, p. 37, Jan. 2018, doi: 10.4103/jpi.jpi_42_18. [5] D. Clunie, A. Fedorov, and M. D. Herrmann, ImagingDataCommons/idc-wsi-conversion: Initial release. Zenodo, 2023. doi: 10.5281/zenodo.8240154.

  PublisherDOI

• DICOM converted whole slide hematoxylin and eosin images of rhabdomyosarcoma from Children's Oncology Group trials

  Zenodo (CERN European Organization for Nuclear Research) · 2023-08-23

  datasetOpen access

  Rhabdomyosarcoma (RMS) is an aggressive soft-tissue sarcoma, which primarily occurs in children and young adults. This dataset contains manifests referring to the hematoxylin and eosin (H&E) stained images in Digital Imaging and Communications in Medicine (DICOM) format available from National Cancer Institute Imaging Data Commons (IDC) [1] (also see IDC Portal at https://imaging.datacommons.cancer.gov) as of data release v16. The original images in vendor-specific format were collected on IRB-approved clinical trials or tissue banking studies from Children’s Oncology Group (COG) patients enrolled on ARST0331, ARST0431, D9602, D9803, and D9902 trials, as described in [2]. Those images, augmented with the metadata describing their content, were provided to the IDC team for the purposes of archival, and were converted into DICOM Whole Slide Microscopy (SM) representation [3], [4] using custom open source scripts and tools available and described here [5]. The resulting converted images were released in IDC in the RMS-Mutation-Prediction collection with the data release v16. To conveniently explore the data available for this dataset, please use this dashboard: https://lookerstudio.google.com/reporting/7f267400-8774-42e1-b5d1-ca11863c52a9. Notebooks demonstrating how to use this data are available here: https://github.com/ImagingDataCommons/IDC-Tutorials/tree/master/notebooks/collections_demos/rms_mutation_prediction. Clinical data accompanying the images is available via SQL interface in IDC BigQuery tables, see details on accessing IDC clinical data in the respective tutorial (https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/clinical_data_intro.ipynb). The images referred to by the accompanying manifests can be explored and visualized using IDC Portal here: https://portal.imaging.datacommons.cancer.gov/explore/. Direct link to open the collection is https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=rms_mutation_prediction. The GCP and AWS manifests provided with this dataset record can be used to download the corresponding files from the IDC Google Cloud Storage (GCS) or Amazon S3 (AWS) buckets free of charge following the instructions available in IDC documentation here: https://learn.canceridc.dev/data/downloading-data. Specifically, you will need to install the s5cmd command line tool on your computer (see instructions at https://github.com/peak/s5cmd#installation), and follow the manifest-specific download instructions accompanying the file list below. If you use the files referenced in the attached manifests, we ask you to please cite this dataset, as well as the publication describing the original dataset [2] and the publication acknowledging IDC [1]. Specific files included in the record are: rms_mutation_prediction_gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: s5cmd --no-sign-request --endpoint-url https://storage.googleapis.com run rms_mutation_prediction_gcs.s5cmd) rms_mutation_prediction_aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: s5cmd --no-sign-request --endpoint-url https://s3.amazonaws.com run rms_mutation_prediction_aws.s5cmd) rms_mutation_prediction_dcf.csv: Gen3-based manifest (see details in https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids). References [1] A. Fedorov et al., "NCI Imaging Data Commons," Cancer Res., vol. 81, no. 16, pp. 4188–4193, Aug. 2021, doi: 10.1158/0008-5472.CAN-21-0950. [2] D. Milewski et al., "Predicting molecular subtype and survival of rhabdomyosarcoma patients using deep learning of H&E images: A report from the Children's Oncology Group," Clin. Cancer Res., vol. 29, no. 2, pp. 364–378, Jan. 2023, doi: 10.1158/1078-0432.CCR-22-1663. [3] National Electrical Manufacturers Association (NEMA), "DICOM PS3.3 - Information Object Definitions: A.32.8 VL Whole Slide Microscopy Image IOD." Accessed: Aug. 11, 2023. [Online]. Available: https://dicom.nema.org/medical/dicom/current/output/html/part03.html#sect_A.32.8 [4] M. D. Herrmann et al., "Implementing the DICOM standard for digital pathology," J. Pathol. Inform., vol. 9, no. 1, p. 37, Jan. 2018, doi: 10.4103/jpi.jpi_42_18. [5] D. Clunie, A. Fedorov, and M. D. Herrmann, ImagingDataCommons/idc-wsi-conversion: Initial release. Zenodo, 2023. doi: 10.5281/zenodo.8240154.

  PublisherDOI

• Initial experience and outcomes with a hybrid extracorporeal membrane oxygenation and cardiopulmonary bypass circuit for lung transplantation

  JTCVS Open · 2023-10-01 · 12 citations

  articleOpen access

  Background: The utilization of extracorporeal life support (ECLS) for intraoperative support during lung transplantation has increased over the past decade. Although veno-arterial extracorporeal membrane oxygenation (VA-ECMO) has recently emerged as the preferred modality over cardiopulmonary bypass (CPB), many centers continue to use both forms of ECLS during lung transplantation. Our novel hybrid VA-ECMO/CPB circuit allows for seamless transition from VA-ECMO to CPB at a significant cost savings compared to a standalone VA-ECMO circuit. This study describes our initial experience and outcomes in the first 100 bilateral lung transplantations using this novel hybrid VA-ECMO/CPB circuit. Methods: Medical records from September 2017 to May 2021 of the first 100 consecutive patients undergoing bilateral lung transplantation with intraoperative hybrid VA-ECMO support were examined retrospectively. We excluded patients with single lung transplants, retransplantations, preoperative ECLS bridging, and veno-venous (VV) ECMO and those supported with CPB only. Perioperative recipient, anesthetic, perfusion variables, and outcomes were assessed. Results: Of the 100 patients supported with VA-ECMO, 19 were converted intraoperatively to CPB. Right ventricular dysfunction was seen in 37% of patients, and the median mean pulmonary artery pressure was 28 mm Hg. No oxygenator clotting was observed with a median heparin dose of 13,000 units in the VA-ECMO group. Primary graft dysfunction grade 3 at 72 hours was observed in 10.1% of all patients and observed 1-year mortality was 4%. Conclusions: The use of a hybrid VA-ECMO/CPB circuit in our institution allows for rapid conversion to CPB with acceptable outcomes across a diverse recipient group at a significantly reduced cost compared to standalone VA-ECMO circuits.

  PublisherOA PDFDOI

Frequent coauthors

• Sheila Dunn

  University of Toronto

  37 shared

• Marsha M. Cohen

  Houston Methodist

  30 shared

• Khaled J. Saleh

  John D. Dingell VA Medical Center

  24 shared

• Ian A. Makey

  WinnMed

  23 shared

• Mathew Thomas

  Mayo Clinic in Florida

  23 shared

• Si M. Pham

  WinnMed

  23 shared

• Archer Kilbourne Martin

  Mayo Clinic in Florida

  20 shared

• William M. Mihalko

  University of Tennessee Health Science Center

  20 shared