WashU weekly Neuroscience publications

Single-cell multi-omic analysis of the vestibular schwannoma ecosystem uncovers a nerve injury-like state
(2024) Nature Communications, 15 (1), art. no. 478, . 

Barrett, T.F.^a , Patel, B.^b , Khan, S.M.^c d , Mullins, R.D.Z.^a e , Yim, A.K.Y.^e , Pugazenthi, S.^b , Mahlokozera, T.^b , Zipfel, G.J.^b f , Herzog, J.A.^a f , Chicoine, M.R.^g , Wick, C.C.^a f , Durakovic, N.^a f , Osbun, J.W.^b , Shew, M.^a f , Sweeney, A.D.^h , Patel, A.J.^h i j , Buchman, C.A.^a f , Petti, A.A.^c d , Puram, S.V.^a e k , Kim, A.H.^b e f

^a Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States
^c Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
^d Brain Tumor Immunology and Immunotherapy Program, Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
^e Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
^f Brain Tumor Center, Washington University School of Medicine/Siteman Cancer Center, St. Louis, MO, United States
^g Department of Neurological Surgery, University of Missouri School of Medicine, Columbia, MO, United States
^h Department of Otolaryngology-Head and Neck Surgery, Baylor College of Medicine, Houston, TX, United States
ⁱ Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
^j Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
^k Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to VS pathogenesis remains poorly understood. In this study, we perform scRNA-seq on 15 VS, with paired scATAC-seq (n = 6) and exome sequencing (n = 12). We identify diverse Schwann cell (SC), stromal, and immune populations in the VS TME and find that repair-like and MHC-II antigen-presenting SCs are associated with myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors reveals Injury-like tumors are associated with larger tumor size, and scATAC-seq identifies transcription factors associated with nerve repair SCs from Injury-like tumors. Ligand-receptor analysis and in vitro experiments suggest that Injury-like VS-SCs recruit myeloid cells via CSF1 signaling. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be therapeutically targeted. © 2023, The Author(s).

Funding details
National Institutes of HealthNIH5R25NS090978-08
National Institute on Deafness and Other Communication DisordersNIDCDT32DC000022
Doris Duke Charitable FoundationDDCF
Foundation for Barnes-Jewish HospitalFBJH

Document Type: Article
Publication Stage: Final
Source: Scopus

Understanding the Biering-Sørensen test: Contributors to extensor endurance in young adults with and without a history of low back pain
(2024) Journal of Electromyography and Kinesiology, 74, art. no. 102854, . 

Shaw, J.^a , Jacobs, J.V.^b , Van Dillen, L.R.^c , Beneck, G.J.^d , Smith, J.A.^a

^a Crean College of Health and Behavioral Sciences, Chapman UniversityCA, United States
^b Rehabilitation and Movement Science, University of VermontVT, United States
^c Program in Physical Therapy, Orthopaedic Surgery, Washington University School of Medicine in St. Louis, St. Louis, WA, United States
^d Department of Physical Therapy, California State University, Long Beach, CA, United States

Abstract
The Biering-Sørensen test is commonly used to assess paraspinal muscle endurance. Research using a single repetition of the test has provided conflicting evidence for the contribution of impaired paraspinal muscle endurance to low back pain (LBP). This study investigated how Sørensen test duration, muscle activation, and muscle fatigability are affected by multiple repetitions of the test and determined predictors of Sørensen test duration in young adults with and without a history of LBP. Sixty-four young individuals performed three repetitions of the Sørensen test. Amplitude of activation and median frequency slope (fatigability) were calculated for the lumbar and thoracic paraspinals and hamstrings. Duration of the test was significantly less for the 3rd repetition in individuals with LBP. In individuals without LBP, test duration was predicted by fatigability of the lumbar paraspinals. In individuals with LBP, Sørensen test duration was predicted by fatigability of the hamstrings and amplitude of activation of the thoracic and lumbar paraspinals. Our findings demonstrate that it is necessary to amplify the difficulty of the Sørensen test to reveal impairments in young, active adults with LBP. Training programs aiming to improve lumbar paraspinal performance should monitor performance of other synergist muscles during endurance exercise. © 2023 Elsevier Ltd

Author Keywords
Biering-Sørensen test;  Endurance;  Low back pain;  Paraspinal

Funding details
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDK01HD092612

Document Type: Article
Publication Stage: Final
Source: Scopus

Contrast response function estimation with nonparametric Bayesian active learning
(2024) Journal of Vision, 24 (1), p. 6. 

Marticorena, D.C.P.^a b , Wong, Q.W.^a , Browning, J.^c , Wilbur, K.^c , Jayakumar, S.^d e , Davey, P.G.^f g , Seitz, A.R.^h , Gardner, J.R.^i j , Barbour, D.L.^a

^a Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
^b dominic.m@wustl.edu
^c Department of Computer Science and Engineering, Washington University, St. Louis, MO, United States
^d Department of Psychology, University of California, Riverside, CA, United States
^e sjaya012@ucr.edu
^f College of Optometry, Western University of Health Sciences, Pomona, CA, United States
^g contact@pinakin-gunvant.com
^h Department of Psychology, Northeastern University, Boston, MA, United States
ⁱ Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States
^j jacobrg@seas.upenn.edu

Abstract
Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential.

Document Type: Article
Publication Stage: Final
Source: Scopus