Arts & Sciences Brown School McKelvey School of Engineering School of Medicine Weekly Publications

WashU weekly Neuroscience publications

Scopus list of publications for January 16, 2023

Conformational plasticity of NaK2K and TREK2 potassium channel selectivity filters” (2023) Nature Communications

Conformational plasticity of NaK2K and TREK2 potassium channel selectivity filters
(2023) Nature Communications, 14 (1), art. no. 89, . 

Matamoros, M.a b , Ng, X.W.a b , Brettmann, J.B.a c , Piston, D.W.a b , Nichols, C.G.a b

a Center for Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO, United States
b Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, United States
c Millipore-Sigma Inc., St. Louis, MO, United States

Abstract
The K+ channel selectivity filter (SF) is defined by TxGYG amino acid sequences that generate four identical K+ binding sites (S1-S4). Only two sites (S3, S4) are present in the non-selective bacterial NaK channel, but a four-site K+-selective SF is obtained by mutating the wild-type TVGDGN SF sequence to a canonical K+ channel TVGYGD sequence (NaK2K mutant). Using single molecule FRET (smFRET), we show that the SF of NaK2K, but not of non-selective NaK, is ion-dependent, with the constricted SF configuration stabilized in high K+ conditions. Patch-clamp electrophysiology and non-canonical fluorescent amino acid incorporation show that NaK2K selectivity is reduced by crosslinking to limit SF conformational movement. Finally, the eukaryotic K+ channel TREK2 SF exhibits essentially identical smFRET-reported ion-dependent conformations as in prokaryotic K+ channels. Our results establish the generality of K+-induced SF conformational stability across the K+ channel superfamily, and introduce an approach to study manipulation of channel selectivity. © 2023, The Author(s).

Funding details
National Institutes of HealthNIHR35 HL140024
Washington University in St. LouisWUSTL
McDonnell Center for Cellular and Molecular Neurobiology, Washington University in St. Louis

Document Type: Article
Publication Stage: Final
Source: Scopus

Evaluating change in body image concerns following a single session digital intervention” (2023) Body Image

Evaluating change in body image concerns following a single session digital intervention
(2023) Body Image, 44, pp. 64-68. 

Nemesure, M.D.a c , Park, C.a , Morris, R.R.d , Chan, W.W.e f , Fitzsimmons-Craft, E.E.g , Rackoff, G.N.h , Fowler, L.A.g , Taylor, C.B.e f , Jacobson, N.C.a b c

a Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
b Department of Biomedical Data Science, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States
c Quantitative Biomedical Sciences Program, Dartmouth College, Lebanon, NH, United States
d Koko, San Francisco, CA, United States
e Stanford University, Stanford, CA, United States
f Palo Alto University, Palo Alto, CA, United States
g Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
h Pennsylvania State University, University ParkPA, United States

Abstract
Many young individuals at risk for eating disorders spend time on social media and frequently search for information related to their body image concerns. In a large randomized study, we demonstrated that a guided chat-based intervention could reduce weight and shape concerns and eating disorder pathology. The goal of the current study was to determine if a modified single session mini-course, derived from the aforementioned chat-based intervention, could reduce body image concerns among individuals using eating disorder related search terms on a social media platform. Over a two-month period of prompting individuals, 525 people followed the link to the web-based application where the intervention was hosted and subsequently completed the mini-course. This resulted in a significant improvement on the one-time body image satisfaction question pre-to post intervention (p <.001) with a moderate effect size (Cohen’s d = 0.54). Additionally, individuals completing the program showed significant improvement on motivation to change their body image (p <.001) with a small effect size (Cohen’s d = 0.28). Additionally, users reported that the program was enjoyable and easy to use. These results suggest that a single session micro-intervention, offered to individuals on social media, can help improve body image. © 2022 Elsevier Ltd

Author Keywords
Body image;  Digital Intervention;  Micro-intervention;  Online Delivery;  Scalability;  Social media

Funding details
National Institute on Drug AbuseNIDA

Document Type: Article
Publication Stage: Final
Source: Scopus

Symptoms that remain after depression treatment in patients with coronary heart disease” (2023) Journal of Psychosomatic Research

Symptoms that remain after depression treatment in patients with coronary heart disease
(2023) Journal of Psychosomatic Research, 165, art. no. 111122, . 

Carney, R.M.a , Freedland, K.E.a , Steinmeyer, B.C.a , Rich, M.W.b

a Departments of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
b Medicine, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Objective: Symptoms which commonly remain after treatment for major depression increase the risk of relapse and recurrence in medically well patients. The same symptoms predict major adverse cardiac events in observational studies of patients with coronary heart disease (CHD). The purpose of this study was to determine the prevalence and predictors of residual depression symptoms in depressed patients with CHD-. Methods: Beck Depression Inventory-II data from two randomized clinical trials and an uncontrolled treatment study of depression in patients with CHD were combined to determine the prevalence and predictors of residual symptoms. Results: Loss of energy, loss of pleasure, loss of interest, fatigue, and difficulty concentrating were the five most common residual symptoms in all three studies. They are also among the most common residual symptoms in medically well patients who are treated for depression. The severity of pre-treatment anxiety predicted the post-treatment persistence of all these symptoms except for loss of energy. Conclusions: The most common post-treatment residual symptoms found in this study of patients with coronary heart disease and comorbid major depression are the same as those that have been reported in previous studies of medically-well depressed patients. This suggests that they may be resistant to standard depression treatments across diverse patient populations. More effective treatments for these symptoms are needed. © 2022 Elsevier Inc.

Author Keywords
Antidepressive agents;  Cognitive behavior therapy;  Coronary heart disease;  Depression;  Depressive disorders

Funding details
National Institutes of HealthNIH
National Heart, Lung, and Blood InstituteNHLBI

Document Type: Article
Publication Stage: Final
Source: Scopus

Childhood adversities and risk of posttraumatic stress disorder and major depression following a motor vehicle collision in adulthood” (2023) Epidemiology and Psychiatric Sciences

Childhood adversities and risk of posttraumatic stress disorder and major depression following a motor vehicle collision in adulthood
(2023) Epidemiology and Psychiatric Sciences, 32, p. e1. 

Ziobrowski, H.N.a , Holt-Gosselin, B.b c , Petukhova, M.V.a , King, A.J.a , Lee, S.a , House, S.L.d , Beaudoin, F.L.e , An, X.f , Stevens, J.S.g , Zeng, D.h , Neylan, T.C.i , Clifford, G.D.j k , Linnstaedt, S.D.f , Germine, L.T.l m n , Bollen, K.A.o , Rauch, S.L.l n p , Haran, J.P.q , Storrow, A.B.r , Lewandowski, C.s , Musey, P.I.t , Hendry, P.L.u , Sheikh, S.u , Jones, C.W.v , Punches, B.E.w x , Kurz, M.C.y z aa , Swor, R.A.ab , Hudak, L.A.ac , Pascual, J.L.ad ae , Seamon, M.J.ae af , Harris, E.ag , Pearson, C.ah , Merchant, R.C.ai , Domeier, R.M.aj , Rathlev, N.K.ak , O’Neil, B.J.al , Sergot, P.am , Sanchez, L.D.ai an , Bruce, S.E.ao , Miller, M.W.ap aq , Pietrzak, R.H.ar as , Joormann, J.b , Barch, D.M.at , Pizzagalli, D.A.n au , Harte, S.E.av aw , Elliott, J.M.ax ay az , Ressler, K.J.n au , McLean, S.A.ba bb , Koenen, K.C.bc , Kessler, R.C.a

a Department of Health Care Policy, Harvard Medical School, Boston, MA, United States
b Department of Psychology, Yale University, New Haven, CT, United States
c Interdepartmental Neuroscience Graduate Program, Yale School of Medicine, New Haven, CT, United States
d Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO, United States
e Department of Emergency Medicine & Department of Health Services, Policy, Practice, Alpert Medical School of Brown University, Rhode Island Hospital and The Miriam Hospital, Providence, RI, United States
f Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel HillNC, United States
g Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
h Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel HillNC, United States
i Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, CA, United States
j Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States
k Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
l Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
m Many Brains Project, Belmont, MA, United States
n Department of Psychiatry, Harvard Medical School, Boston, MA, United States
o Department of Psychology and Neuroscience & Department of Sociology, University of North Carolina at Chapel Hill, Chapel HillNC, United States
p Department of Psychiatry, McLean Hospital, Belmont, MA, United States
q Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
r Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
s Department of Emergency Medicine, Henry Ford Health System, Detroit, MI, United States
t Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
u Department of Emergency Medicine, University of Florida College of Medicine -Jacksonville, Jacksonville, FL, United States
v Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, NJ, United States
w Department of Emergency Medicine, Ohio State University College of Medicine, Columbus, OH, United States
x Ohio State University College of Nursing, Columbus, OH, United States
y Department of Emergency Medicine, University of Alabama School of Medicine, Birmingham, AL, United States
z Department of Surgery, Division of Acute Care Surgery, University of Alabama School of Medicine, Birmingham, AL, United States
aa Center for Injury Science, University of Alabama at Birmingham, Birmingham, AL, United States
ab Department of Emergency Medicine, Oakland University William Beaumont School of Medicine, Rochester, MI, United States
ac Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, United States
ad Department of Surgery, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States
ae Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
af Department of Surgery, Division of Traumatology, Surgical Critical Care and Emergency Surgery, University of Pennsylvania, Philadelphia, PA, United States
ag Department of Emergency Medicine, Einstein Medical Center, Philadelphia, PA, United States
ah Department of Emergency Medicine, Wayne State University, Ascension St. John Hospital, Detroit, MI, United States
ai Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, MA, United States
aj Department of Emergency Medicine, Saint Joseph Mercy Hospital, Ypsilanti, MI, United States
ak Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA, United States
al Department of Emergency Medicine, Wayne State University, Detroit Receiving Hospital, Detroit, MI, United States
am Department of Emergency Medicine, McGovern Medical School at UTHealth, Houston, TX, United States
an Department of Emergency Medicine, Harvard Medical School, Boston, MA, United States
ao Department of Psychological Sciences, University of Missouri – St. Louis, St. Louis, MO, United States
ap National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, United States
aq Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
ar National Center for PTSD, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, United States
as Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
at Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
au McLean Hospital, Belmont, MA, United States
av Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
aw Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI, United States
ax Kolling Institute, University of Sydney, St Leonards, NSW, Australia
ay Faculty of Medicine and Health, University of Sydney, Northern Sydney Local Health DistrictNSW, Australia
az Physical Therapy & Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
ba Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel HillNC, United States
bb Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel HillNC, United States
bc Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States

Abstract
AIMS: Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions. METHODS: Data came from n = 999 patients ages 18-75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models. RESULTS: Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31-1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65-2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43-2.87) and bullying (RR = 1.44; 95% CI = 0.99-2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE. CONCLUSIONS: Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Author Keywords
Depression;  mental health;  post traumatic stress disorder;  Trauma

Document Type: Article
Publication Stage: Final
Source: Scopus

Use of serial smartphone-based assessments to characterize diverse neuropsychiatric symptom trajectories in a large trauma survivor cohort” (2023) Translational Psychiatry

Use of serial smartphone-based assessments to characterize diverse neuropsychiatric symptom trajectories in a large trauma survivor cohort
(2023) Translational Psychiatry, 13 (1), art. no. 4, . 

Beaudoin, F.L.a b , An, X.c , Basu, A.d , Ji, Y.e , Liu, M.e f , Kessler, R.C.g , Doughtery, R.F.h , Zeng, D.f , Bollen, K.A.i , House, S.L.j , Stevens, J.S.k , Neylan, T.C.l , Clifford, G.D.m n , Jovanovic, T.o , Linnstaedt, S.D.c , Germine, L.T.p q r , Rauch, S.L.p r s , Haran, J.P.t , Storrow, A.B.u , Lewandowski, C.v , Musey, P.I., Jr.w , Hendry, P.L.x , Sheikh, S.x , Jones, C.W.y , Punches, B.E.z aa , Kurz, M.C.ab ac ad , Swor, R.A.ae , Murty, V.P.af , McGrath, M.E.ag , Hudak, L.A.ah , Pascual, J.L.ai aj , Datner, E.M.ak al , Chang, A.M.am , Pearson, C.an , Peak, D.A.ao , Merchant, R.C.ap , Domeier, R.M.aq , Rathlev, N.K.ar , Neil, B.J.O.an , Sergot, P.as , Sanchez, L.D.at au , Bruce, S.E.av , Baker, J.T.h , Joormann, J.aw , Miller, M.W.ax ay , Pietrzak, R.H.az ba , Barch, D.M.bb , Pizzagalli, D.A.r bc , Sheridan, J.F.bd be , Smoller, J.W.bf bg , Harte, S.E.bh bi , Elliott, J.M.bj bk bl , Koenen, K.C.d , Ressler, K.J.r bc , McLean, S.A.e bm

a Department of Epidemiology, Brown University, Providence, RI, United States
b Department of Emergency Medicine, Brown University, Providence, RI, United States
c Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
d Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
e Institute for Trauma Recovery, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
f Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States
g Department of Health Care Policy, Harvard Medical School, Boston, MA, United States
h Mindstrong Health, Mountain View, CA, United States
i Department of Psychology and Neuroscience & Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
j Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO, United States
k Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
l Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, CA, United States
m Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States
n Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
o Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MA, United States
p Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
q The Many Brains Project, Belmont, MA, United States
r Department of Psychiatry, Harvard Medical School, Boston, MA, United States
s Department of Psychiatry, McLean Hospital, Belmont, MA, United States
t Department of Emergency Medicine, University of Massachusetts Medical School, Worcester, MA, United States
u Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
v Department of Emergency Medicine, Henry Ford Health System, Detroit, MI, United States
w Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
x Department of Emergency Medicine, University of Florida College of Medicine -Jacksonville, Jacksonville, FL, United States
y Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, NJ, United States
z Department of Emergency Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, United States
aa College of Nursing, University of Cincinnati, Cincinnati, OH, United States
ab Department of Emergency Medicine, University of Alabama School of Medicine, Birmingham, AL, United States
ac Department of Surgery, Division of Acute Care Surgery, University of Alabama School of Medicine, Birmingham, AL, United States
ad Center for Injury Science, University of Alabama at Birmingham, Birmingham, AL, United States
ae Department of Emergency Medicine, Oakland University William Beaumont School of Medicine, Rochester, MI, United States
af Department of Psychology, Temple University, Philadelphia, PA, United States
ag Department of Emergency Medicine, Boston Medical Center, Boston, MA, United States
ah Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, United States
ai Department of Surgery, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States
aj Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
ak Department of Emergency Medicine, Einstein Healthcare Network, Philadelphia, PA, United States
al Department of Emergency Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
am Department of Emergency Medicine, Jefferson University Hospitals, Philadelphia, PA, United States
an Department of Emergency Medicine, Wayne State University, Detroit, MI, United States
ao Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, United States
ap Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, MA, United States
aq Department of Emergency Medicine, Saint Joseph Mercy Hospital, Ypsilanti, MI, United States
ar Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA, United States
as Department of Emergency Medicine, McGovern Medical School, University of Texas Health, Houston, TX, United States
at Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
au Department of Emergency Medicine, Harvard Medical School, Boston, MA, United States
av Department of Psychological Sciences, University of Missouri – St. Louis, St. Louis, MO, United States
aw Department of Psychology, Yale University, West Haven, CT, United States
ax National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, United States
ay Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
az National Center for PTSD, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, United States
ba Department of Psychiatry, Yale School of Medicine, West Haven, CT, United States
bb Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
bc Division of Depression and Anxiety, McLean Hospital, Belmont, MA, United States
bd Department of Biosciences, OSU Wexner Medical Center, Columbus, OH, United States
be Institute for Behavioral Medicine Research, OSU Wexner Medical Center, Columbus, OH, United States
bf Department of Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
bg Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, United States
bh Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
bi Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI, United States
bj Kolling Institute of Medical Research, University of Sydney, St Leonards, NSW, Australia
bk Faculty of Medicine and Health, University of Sydney, Northern Sydney Local, Health DistrictNSW, Australia
bl Physical Therapy & Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
bm Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

Abstract
The authors sought to characterize adverse posttraumatic neuropsychiatric sequelae (APNS) symptom trajectories across ten symptom domains (pain, depression, sleep, nightmares, avoidance, re-experiencing, anxiety, hyperarousal, somatic, and mental/fatigue symptoms) in a large, diverse, understudied sample of motor vehicle collision (MVC) survivors. More than two thousand MVC survivors were enrolled in the emergency department (ED) and completed a rotating battery of brief smartphone-based surveys over a 2-month period. Measurement models developed from survey item responses were used in latent growth curve/mixture modeling to characterize homogeneous symptom trajectories. Associations between individual trajectories and pre-trauma and peritraumatic characteristics and traditional outcomes were compared, along with associations within and between trajectories. APNS across all ten symptom domains were common in the first two months after trauma. Many risk factors and associations with high symptom burden trajectories were shared across domains. Both across and within traditional diagnostic boundaries, APNS trajectory intercepts, and slopes were substantially correlated. Across all domains, symptom severity in the immediate aftermath of trauma (trajectory intercepts) had the greatest influence on the outcome. An interactive data visualization tool was developed to allow readers to explore relationships of interest between individual characteristics, symptom trajectories, and traditional outcomes (http://itr.med.unc.edu/aurora/parcoord/). Individuals presenting to the ED after MVC commonly experience a broad constellation of adverse posttraumatic symptoms. Many risk factors for diverse APNS are shared. Individuals diagnosed with a single traditional outcome should be screened for others. The utility of multidimensional categorizations that characterize individuals across traditional diagnostic domains should be explored. © 2023, The Author(s).

Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMHU01MH110925
MAYDAY Fund

Document Type: Article
Publication Stage: Final
Source: Scopus

Low-risk meningioma: Initial outcomes from NRG Oncology/RTOG 0539” (2023) Neuro-oncology

Low-risk meningioma: Initial outcomes from NRG Oncology/RTOG 0539
(2023) Neuro-oncology, 25 (1), pp. 137-145. 

Rogers, C.L.a , Pugh, S.L.b , Vogelbaum, M.A.c , Perry, A.d , Ashby, L.S.e , Modi, J.M.f , Alleman, A.M.g , Barani, I.J.h , Braunstein, S.i , Bovi, J.A.j , de Groot, J.F.k , Whitton, A.C.l , Lindhorst, S.M.m , Deb, N.n , Shrieve, D.C.o , Shu, H.-K.p , Bloom, B.q , Machtay, M.r , Mishra, M.V.s , Robinson, C.G.t , Won, M.b , Mehta, M.P.u

a GammaWest Cancer Services, Salt Lake City, UT, United States
b NRG Oncology Statistics and Data Management Center, Philadelphia, PA, United States
c Moffitt Cancer Center, Tampa, FL, United States
d University of California, Neuropathology, San Francisco, CA, United States
e Barrow Neurological Institute, Neurology, Phoenix, AZ, United States
f MidState Medical Center, Radiology, Meriden, CT, United States
g University of Oklahoma, Radiology, Oklahoma City, OK, United States
h Barrow Neurological Institute, Radiation Oncology, Phoenix, AZ, United States
i University of California, Radiation Oncology, San Francisco, CA, United States
j Medical College of Wisconsin, Radiation Oncology, Milwaukee, WI, United States
k University of California, Neuro Oncology, San Francisco, CA, United States
l Juravinski Cancer Centre, Radiation Oncology, Hamilton, Ontario, Canada
m Medical University of South Carolina, Neuro Oncology, Charleston, SC, United States
n St. Luke’s Hospital-Anderson Campus Cancer Center, Easton, PA, United States
o Huntsman Cancer Institute, Radiation Oncology, University of Utah, Salt Lake City, UT, United States
p Winship Cancer Institute at Emory University, Radiation Oncology, Atlanta, GA, United States
q Radiation Oncology, Northwell HealthNew Hyde ParkNY, United States
r Penn State Cancer Institute, Radiation Oncology, Hershey, PA, United States
s University of Maryland, Radiation Oncology, Baltimore, MD, United States
t Washington University, Radiation Oncology, St. Louis, MO, United States
u Miami Cancer Institute, Baptist Health South Florida, Miami, FL, United States

Abstract
BACKGROUND: Three- and five-year progression-free survival (PFS) for low-risk meningioma managed with surgery and observation reportedly exceeds 90%. Herewith we summarize outcomes for low-risk meningioma patients enrolled on NRG/RTOG 0539. METHODS: This phase II trial allocated patients to one of three groups per World Health Organization grade, recurrence status, and resection extent. Low-risk patients had either gross total (GTR) or subtotal resection (STR) for a newly diagnosed grade 1 meningioma and were observed after surgery. The primary endpoint was 3-year PFS. Adverse events (AEs) were scored using Common Terminology Criteria for Adverse Events (CTCAE) version 3. RESULTS: Among 60 evaluable patients, the median follow-up was 9.1 years. The 3-, 5-, and 10-year rates were 91.4% (95% CI, 84.2 to 98.6), 89.4% (95% CI, 81.3 to 97.5), 85.0% (95% CI, 75.3 to 94.7) for PFS and 98.3% (95% CI, 94.9 to 100), 98.3%, (95% CI, 94.9 to 100), 93.8% (95% CI, 87.0 to 100) for overall survival (OS), respectively. With centrally confirmed GTR, 3/5/10y PFS and OS rates were 94.3/94.3/87.6% and 97.1/97.1/90.4%. With STR, 3/5/10y PFS rates were 83.1/72.7/72.7% and 10y OS 100%. Five patients reported one grade 3, four grade 2, and five grade 1 AEs. There were no grade 4 or 5 AEs. CONCLUSIONS: These results prospectively validate high PFS and OS for low-risk meningioma managed surgically but raise questions regarding optimal management following STR, a subcohort that could potentially benefit from adjuvant therapy. © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Author Keywords
cooperative group trial;  meningioma;  observation;  surgery;  WHO grade 1 (benign)

Document Type: Article
Publication Stage: Final
Source: Scopus

Mitochondrial haplogroups and cognitive progression in Parkinson’s disease” (2023) Brain: A Journal of Neurology

Mitochondrial haplogroups and cognitive progression in Parkinson’s disease
(2023) Brain: A Journal of Neurology, 146 (1), pp. 42-49. 

Liu, G.a , Ni, C.a , Zhan, J.a , Li, W.a , Luo, J.a , Liao, Z.b c , Locascio, J.J.b c d , Xian, W.e , Chen, L.e , Pei, Z.e , Corvol, J.-C.f , Maple-Grødem, J.g h , Campbell, M.C.i , Elbaz, A.j , Lesage, S.f , Brice, A.f , Hung, A.Y.d , Schwarzschild, M.A.d , Hayes, M.T.k , Wills, A.-M.d , Ravina, B.l , Shoulson, I.m , Taba, P.n o , Kõks, S.p q , Beach, T.G.r , Cormier-Dequaire, F.f , Alves, G.g h s , Tysnes, O.-B.t u , Perlmutter, J.S.i v w , Heutink, P.x , van Hilten, J.J.y , Barker, R.A.z aa , Williams-Gray, C.H.z , Scherzer, C.R.b c d k , International Genetics of Parkinson Disease Progression (IGPP) Consortiumab

a Neurobiology Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
b Brigham and Women’s Hospital and Harvard Medical School, APDA Center for Advanced Parkinson Research, Boston, MA 02115, United States
c Neurogenomics Lab, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA 02115, United States
d Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
e Department of Neurology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
f Sorbonne Université, Institut du Cerveau – Paris Brain Institute – ICM, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Département de Neurologie et de Génétique, Hôpital Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Paris, F-75013, France
g Norwegian Centre for Movement Disorders, Stavanger University Hospital, Stavanger, 4068, Norway
h Department of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Stavanger, 4021, Norway
i Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
j Paris-Saclay University, UVSQ, Inserm, Gustave Roussy, CESP, Villejuif, F94805, France
k Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, United States
l Praxis Precision Medicines, Cambridge, MA 02142, United States
m Department of Neurology, Center for Health and Technology, University of Rochester, Rochester, NY 14642, USA
n Department of Neurology and Neurosurgery, Institute of Clinical Medicine, University of TartuTartu 50406, Estonia
o Neurology Clinic, Tartu University HospitalTartu 50406, Estonia
p Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Murdoch, Perth, WA 6150, Australia
q Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
r Banner Sun Health Research Institute, Sun City, United States
s Department of Neurology, Stavanger University Hospital, Stavanger, 4068, Norway
t Department of Neurology, Haukeland University Hospital, Bergen, 5020, Norway
u Department of Clinical Medicine, University of Bergen, Bergen, 5020, Norway
v Departments of Radiology and Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
w Program of Physical Therapy and Program of Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
x German Center for Neurodegenerative diseases (DZNE), 72076 Tübingen, Germany
y Department of Neurology, Leiden University Medical Center, ZA Leiden, 2333, Netherlands
z John Van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0PY, United Kingdom
aa Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 0AW, United Kingdom

Abstract
Mitochondria are a culprit in the onset of Parkinson’s disease, but their role during disease progression is unclear. Here we used Cox proportional hazards models to exam the effect of variation in the mitochondrial genome on longitudinal cognitive and motor progression over time in 4064 patients with Parkinson’s disease. Mitochondrial macro-haplogroup was associated with reduced risk of cognitive disease progression in the discovery and replication population. In the combined analysis, patients with the super macro-haplogroup J, T, U# had a 41% lower risk of cognitive progression with P = 2.42 × 10-6 compared to those with macro-haplogroup H. Exploratory analysis indicated that the common mitochondrial DNA variant, m.2706A>G, was associated with slower cognitive decline with a hazard ratio of 0.68 (95% confidence interval 0.56-0.81) and P = 2.46 × 10-5. Mitochondrial haplogroups were not appreciably linked to motor progression. This initial genetic survival study of the mitochondrial genome suggests that mitochondrial haplogroups may be associated with the pace of cognitive progression in Parkinson’s disease over time. © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Author Keywords
cognitive progression;  mitochondrial haplogroups;  Parkinson’s disease

Document Type: Article
Publication Stage: Final
Source: Scopus

Olutasidenib (FT-2102) in patients with relapsed or refractory IDH1-mutant glioma: A multicenter, open-label, phase Ib/II trial” (2023) Neuro-oncology

Olutasidenib (FT-2102) in patients with relapsed or refractory IDH1-mutant glioma: A multicenter, open-label, phase Ib/II trial
(2023) Neuro-oncology, 25 (1), pp. 146-156. Cited 3 times.

de la Fuente, M.I.a , Colman, H.b , Rosenthal, M.c , Van Tine, B.A.d , Levacic, D.e , Walbert, T.f , Gan, H.K.g , Vieito, M.h , Milhem, M.M.i , Lipford, K.j , Forsyth, S.j , Guichard, S.M.j , Mikhailov, Y.j , Sedkov, A.j , Brevard, J.j , Kelly, P.F.j , Mohamed, H.j , Monga, V.i

a Sylvester Comprehensive Cancer Center and Department of Neurology, University of Miami, Miami, FL, United States
b Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States
c Peter MacCallum Cancer Centre MelbourneVIC, Australia
d Washington University in St. Louis School of Medicine, St. Louis, MO, United States
e Baylor and Scott White Vasicek Cancer Center, Baylor University Temple, Temple, TX, United States
f Henry Ford Cancer Institute, Henry Ford Health System and Wayne State University, Detroit, MI, United States
g Olivia Newton-John Cancer Wellness and Research Centre Austin Hospital, Heidelberg, VIC, Australia
h Vall d’Hebron Institute of Oncology, Barcelona, Spain
i Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, United States
j Forma Therapeutics, Inc., Watertown, MA, United States

Abstract
BACKGROUND: Olutasidenib (FT-2102) is a highly potent, orally bioavailable, brain-penetrant and selective inhibitor of mutant isocitrate dehydrogenase 1 (IDH1). The aim of the study was to determine the safety and clinical activity of olutasidenib in patients with relapsed/refractory gliomas harboring an IDH1R132X mutation. METHODS: This was an open-label, multicenter, nonrandomized, phase Ib/II clinical trial. Eligible patients (≥18 years) had histologically confirmed IDH1R132X-mutated glioma that relapsed or progressed on or following standard therapy and had measurable disease. Patients received olutasidenib, 150 mg orally twice daily (BID) in continuous 28-day cycles. The primary endpoints were dose-limiting toxicities (DLTs) (cycle 1) and safety in phase I and objective response rate using the Modified Response Assessment in Neuro-Oncology criteria in phase II. RESULTS: Twenty-six patients were enrolled and followed for a median 15.1 months (7.3‒19.4). No DLTs were observed in the single-agent glioma cohort and the pharmacokinetic relationship supported olutasidenib 150 mg BID as the recommended phase II dose. In the response-evaluable population, disease control rate (objective response plus stable disease) was 48%. Two (8%) patients demonstrated a best response of partial response and eight (32%) had stable disease for at least 4 months. Grade 3‒4 adverse events (≥10%) included alanine aminotransferase increased and aspartate aminotransferase increased (three [12%], each). CONCLUSIONS: Olutasidenib 150 mg BID was well tolerated in patients with relapsed/refractory gliomas harboring an IDH1R132X mutation and demonstrated preliminary evidence of clinical activity in this heavily pretreated population. © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

Author Keywords
brain penetration;  glioma;  IDH1;  mutant;  olutasidenib

Document Type: Article
Publication Stage: Final
Source: Scopus

Individual differences in naturalistic learning link negative emotionality to the development of anxiety” (2023) Science Advances

Individual differences in naturalistic learning link negative emotionality to the development of anxiety
(2023) Science Advances, 9 (1), p. eadd2976. 

Villano, W.J.a , Kraus, N.I.a , Reneau, T.R.b , Jaso, B.A.c , Otto, A.R.d , Heller, A.S.a

a Department of Psychology, University of Miami, Coral Gables, FL, United States
b Department of Psychological and Brain Sciences, Washington University in St. LouisMO, United States
c Center for Anxiety and Related Disorders, Boston University, Boston, MA, United States
d Department of Psychology, McGill University, Montreal, Canada

Abstract
Organisms learn from prediction errors (PEs) to predict the future. Laboratory studies using small financial outcomes find that humans use PEs to update expectations and link individual differences in PE-based learning to internalizing disorders. Because of the low-stakes outcomes in most tasks, it is unclear whether PE learning emerges in naturalistic, high-stakes contexts and whether individual differences in PE learning predict psychopathology risk. Using experience sampling to assess 625 college students’ expected exam grades, we found evidence of PE-based learning and a general tendency to discount negative PEs, an “optimism bias.” However, individuals with elevated negative emotionality, a personality trait linked to the development of anxiety disorders, displayed a global pessimism and learning differences that impeded accurate expectations and predicted future anxiety symptoms. A sensitivity to PEs combined with an aversion to negative PEs may result in a pessimistic and inaccurate model of the world, leading to anxiety.

Document Type: Article
Publication Stage: Final
Source: Scopus

Changes in Distribution of Severe Neurologic Involvement in US Pediatric Inpatients With COVID-19 or Multisystem Inflammatory Syndrome in Children in 2021 vs 2020” (2023) JAMA Neurology

Changes in Distribution of Severe Neurologic Involvement in US Pediatric Inpatients With COVID-19 or Multisystem Inflammatory Syndrome in Children in 2021 vs 2020
(2023) JAMA Neurology, 80 (1), pp. 91-98. 

LaRovere, K.L.a , Poussaint, T.Y.b , Young, C.C.c , Newhams, M.M.c , Kucukak, S.c , Irby, K.d , Kong, M.e , Schwartz, S.P.f , Walker, T.C.f , Bembea, M.M.g , Wellnitz, K.h , Havlin, K.M.i , Cvijanovich, N.Z.j , Hall, M.W.k , Fitzgerald, J.C.l , Schuster, J.E.m , Hobbs, C.V.n , Halasa, N.B.o , Singh, A.R.p , Mack, E.H.q , Bradford, T.T.r , Gertz, S.J.s , Schwarz, A.J.t , Typpo, K.V.u , Loftis, L.L.v , Giuliano, J.S., Jrw , Horwitz, S.M.x , Biagas, K.V.y , Clouser, K.N.z , Rowan, C.M.aa , Maddux, A.B.ab , Soma, V.L.ac , Babbitt, C.J.ad , Aguiar, C.L.ae , Kolmar, A.R.af , Heidemann, S.M.ag , Harvey, H.ah , Zambrano, L.D.ai , Campbell, A.P.ai , Randolph, A.G.c aj , Overcoming COVID-19 Investigatorsak

a Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
b Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
c Division of Critical Care Medicine, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children’s Hospital, Boston, MA, United States
d Section of Pediatric Critical Care, Department of Pediatrics, Arkansas Children’s Hospital, Little Rock
e Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Alabama at Birmingham
f Department of Pediatrics, University of North Carolina at Chapel Hill Children’s Hospital ,Chapel Hill
g Division of Pediatric Anesthesiology and Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, Liberia
h Division of Pediatric Critical Care, Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, United States
i Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Louisville, Norton Children’s Hospital, Louisville, KY, United States
j Division of Critical Care Medicine, UCSF Benioff Children’s Hospital, Oakland, CA, United States
k Division of Critical Care Medicine, Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
l Division of Critical Care, Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
m Division of Pediatric Infectious Diseases, Department of Pediatrics, Children’s Mercy Kansas City, Kansas City, MO, United States
n Division of Infectious Diseases, Departments of Pediatrics and Microbiology, University of Mississippi Medical Center, Jackson, United States
o Division of Pediatric Infectious Diseases, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States
p Pediatric Critical Care Division, Maria Fareri Children’s Hospital at Westchester Medical Center, New York Medical College, Valhalla, United States
q Division of Pediatric Critical Care Medicine, Medical University of South Carolina, Charleston, United States
r Division of Cardiology, Department of Pediatrics, Louisiana State University Health Sciences Center, Children’s Hospital of New Orleans, New Orleans, United States
s Division of Pediatric Critical Care, Department of Pediatrics, Cooperman Barnabas Medical Center, Livingston, NJ, United States
t Division of Critical Care Medicine, Children’s Health Orange County (CHOC), Orange, CA, United States
u Department of Pediatrics and Banner Children’s at Diamond Children’s Medical Center, University of Arizona, Tucson, United States
v Section of Critical Care Medicine, Department of Pediatrics, Texas Children’s Hospital, Houston, United States
w Division of Critical Care, Department of Pediatrics, Yale University School of Medicine, New Haven, CT, United States
x Division of Pediatric Critical Care Medicine, Department of Pediatrics, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey
y Department of Pediatrics, Stony Brook University Renaissance School of Medicine, Stony BrookNY, United States
z Department of Pediatrics, Joseph M. Sanzari Children’s Hospital at Hackensack University Medical Center, Hackensack, NJ, United States
aa Division of Pediatric Critical Care Medicine, Department of Pediatrics, Indiana University School of Medicine, Riley Hospital for Children, Indianapolis, United States
ab Section of Critical Care Medicine, Department of Pediatrics, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, United States
ac Division of Pediatric Infectious Diseases, Department of Pediatrics, New York University Grossman School of MedicineNY, United States
ad Miller Children’s and Women’s Hospital of Long Beach, Long BeachCA, United States
ae Division of Pediatric Rheumatology, Department of Pediatrics, Eastern Virginia Medical School, Children’s Hospital of The King’s Daughters, Norfolk, United Kingdom
af Division of Critical Care, Department of Pediatrics, Washington University School of Medicine in St Louis, St Louis, MO, United States
ag Division of Pediatric Critical Care Medicine, Department of Pediatrics, Central Michigan University, Detroit, United States
ah Division of Pediatric Critical Care, Rady Children’s Hospital, San Diego, CA, United States
ai COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
aj Departments of Anaesthesia and Pediatrics, Harvard Medical School, Boston, MA, United States

Abstract
Importance: In 2020 during the COVID-19 pandemic, neurologic involvement was common in children and adolescents hospitalized in the United States for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related complications. Objective: To provide an update on the spectrum of SARS-CoV-2-related neurologic involvement among children and adolescents in 2021. Design, Setting, and Participants: Case series investigation of patients reported to public health surveillance hospitalized with SARS-CoV-2-related illness between December 15, 2020, and December 31, 2021, in 55 US hospitals in 31 states with follow-up at hospital discharge. A total of 2253 patients were enrolled during the investigation period. Patients suspected of having multisystem inflammatory syndrome in children (MIS-C) who did not meet criteria (n = 85) were excluded. Patients (<21 years) with positive SARS-CoV-2 test results (reverse transcriptase-polymerase chain reaction and/or antibody) meeting criteria for MIS-C or acute COVID-19 were included in the analysis. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: Patients with neurologic involvement had acute neurologic signs, symptoms, or diseases on presentation or during hospitalization. Life-threatening neurologic involvement was adjudicated by experts based on clinical and/or neuroradiological features. Type and severity of neurologic involvement, laboratory and imaging data, vaccination status, and hospital discharge outcomes (death or survival with new neurologic deficits). Results: Of 2168 patients included (58% male; median age, 10.3 years), 1435 (66%) met criteria for MIS-C, and 476 (22%) had documented neurologic involvement. Patients with neurologic involvement vs without were older (median age, 12 vs 10 years) and more frequently had underlying neurologic disorders (107 of 476 [22%] vs 240 of 1692 [14%]). Among those with neurologic involvement, 42 (9%) developed acute SARS-CoV-2-related life-threatening conditions, including central nervous system infection/demyelination (n = 23; 15 with possible/confirmed encephalitis, 6 meningitis, 1 transverse myelitis, 1 nonhemorrhagic leukoencephalopathy), stroke (n = 11), severe encephalopathy (n = 5), acute fulminant cerebral edema (n = 2), and Guillain-Barré syndrome (n = 1). Ten of 42 (24%) survived with new neurologic deficits at discharge and 8 (19%) died. Among patients with life-threatening neurologic conditions, 15 of 16 vaccine-eligible patients (94%) were unvaccinated. Conclusions and Relevance: SARS-CoV-2-related neurologic involvement persisted in US children and adolescents hospitalized for COVID-19 or MIS-C in 2021 and was again mostly transient. Central nervous system infection/demyelination accounted for a higher proportion of life-threatening conditions, and most vaccine-eligible patients were unvaccinated. COVID-19 vaccination may prevent some SARS-CoV-2-related neurologic complications and merits further study.

Document Type: Article
Publication Stage: Final
Source: Scopus

Intelligibility as a measure of speech perception: Current approaches, challenges, and recommendations” (2023) Journal of the Acoustical Society of America

Intelligibility as a measure of speech perception: Current approaches, challenges, and recommendations
(2023) Journal of the Acoustical Society of America, 153 (1), pp. 68-76. 

Baese-Berk, M.M.a , Levi, S.V.b , Van Engen, K.J.c

a Department of Linguistics, University of Oregon, Eugene, OR 97403, United States
b Department of Communicative Sciences and Disorders, New York University, New York, NY 10012, United States
c Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, United States

Abstract
Intelligibility measures, which assess the number of words or phonemes a listener correctly transcribes or repeats, are commonly used metrics for speech perception research. While these measures have many benefits for researchers, they also come with a number of limitations. By pointing out the strengths and limitations of this approach, including how it fails to capture aspects of perception such as listening effort, this article argues that the role of intelligibility measures must be reconsidered in fields such as linguistics, communication disorders, and psychology. Recommendations for future work in this area are presented. © 2023 Acoustical Society of America.

Funding details
National Science FoundationNSFBCS-2020805
James S. McDonnell FoundationJSMFBCS-2146993

Document Type: Article
Publication Stage: Final
Source: Scopus

Facility patient volume and survival among individuals diagnosed with malignant central nervous system tumors” (2023) Journal of Neuro-Oncology

Facility patient volume and survival among individuals diagnosed with malignant central nervous system tumors
(2023) Journal of Neuro-Oncology, . 

Johnson, K.J.a , Barnes, J.M.b , Delavar, A.c , O’Connell, C.P.a , Wang, X.a

a Brown School, Washington University in St. Louis, Campus Box 1196, One Brookings Drive, St. Louis, MO 63130, United States
b Department of Radiation Oncology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
c University of California San Diego School of Medicine, La Jolla, San Diego, CA 92093, United States

Abstract
Purpose: Prior research indicates that the volume of central nervous system (CNS) tumor patients seen by a facility is associated with outcomes. However, most studies have focused on short-term survival and specific CNS tumor subtypes. Our objective was to examine whether facility CNS tumor patient volume is associated with longer-term CNS tumor survival overall and by subtype. Methods: We obtained National Cancer Database (NCDB) data including individuals diagnosed with CNS tumors from 2004 to 2016. Analyses were stratified by age group (0–14, 15–39, 40–64, and ≥ 65 years) and tumor type. We used Cox Proportional Hazards (PH) regression and restricted mean survival time (RMST) analyses to examine associations between survival and facility patient volume percentile category adjusting for potential confounding factors. Results: Our analytic dataset included data from 130,830 individuals diagnosed with malignant first primary CNS tumors. We found a consistently reduced hazard rate of death across age groups for individuals reported by higher vs. lower (&gt; 95th vs. ≤ 70th percentile) volume facilities (hazard ratio (HR)0–14 = 0.78, 95% confidence interval (CI) 0.64–0.95; HR15–39 = 0.87, 95% CI 0.78–0.96; HR40–64 = 0.82, 95% CI 0.76–0.88; HR≥65 = 0.80, 95% CI 0.75–0.86). Significantly longer survival times within 5 years for higher vs. lower volume facilities were observed ranging from 1.20 months (15–39) to 3.08 months (40–64) higher. Associations varied by CNS tumor subtype for all age groups. Conclusions: These results suggest facility factors influence CNS tumor survival with longer survival for patients reported by higher volume facilities. Understanding these factors will be critical to developing strategies that eliminate modifiable differences in survival times. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Adolescent;  Central nervous system tumors;  Pediatric;  Volume effect

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Diffusion basis spectrum imaging predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy” (2023) Spine Journal

Diffusion basis spectrum imaging predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy
(2023) Spine Journal, . 

Zhang, J.K.a , Jayasekera, D.b , Javeed, S.a , Greenberg, J.K.a , Blum, J.c , Dibble, C.F.a , Sun, P.d , Song, S.-K.c , Ray, W.Z.a

a Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO 63110, United States
b Department of Biomedical Engineering, Washington University McKelvey School of Engineering, Saint Louis, MO 63130, United States
c Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
d Department of Imaging Physics, UT MD Anderson Cancer Center, Houston, TX 77030, United States

Abstract
BACKGROUND CONTEXT: A major shortcoming in improving care for cervical spondylotic myelopathy (CSM) patients is the lack of robust quantitative imaging tools to guide surgical decision-making. Diffusion basis spectrum imaging (DBSI), an advanced diffusion-weighted MRI technique, provides objective assessments of white matter tract integrity that may help prognosticate outcomes in patients undergoing surgery for CSM. PURPOSE: To examine the ability of DBSI to predict clinically important CSM outcome measures at 2-years follow-up. STUDY DESIGN/SETTING: Prospective cohort study. PATIENT SAMPLE: Patients undergoing decompressive cervical surgery for CSM. OUTCOME MEASURES: Neurofunctional status was assessed by the mJOA, MDI, and DASH. Quality-of-life was measured by the SF-36 PCS and SF-36 MCS. The NDI evaluated self-reported neck pain, and patient satisfaction was assessed by the NASS satisfaction index. METHODS: Fifty CSM patients who underwent cervical decompressive surgery were enrolled. Preoperative DBSI metrics assessed white matter tract integrity through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity. To evaluate extra-axonal diffusion, DBSI measures restricted and nonrestricted fractions. Patient-reported outcome measures were evaluated preoperatively and up to 2-years follow-up. Support vector machine classification algorithms were used to predict surgical outcomes at 2-years follow-up. Specifically, three feature sets were built for each of the seven clinical outcome measures (eg, mJOA), including clinical only, DBSI only, and combined feature sets. RESULTS: Twenty-seven mild (mJOA 15–17), 12 moderate (12–14) and 11 severe (0–11) CSM patients were enrolled. Twenty-four (60%) patients underwent anterior decompressive surgery compared with 16 (40%) posterior approaches. The mean (SD) follow-up was 23.2 (5.6, range 6.1–32.8) months. Feature sets built on combined data (ie, clinical+DBSI metrics) performed significantly better for all outcome measures compared with those only including clinical or DBSI data. When predicting improvement in the mJOA, the clinically driven feature set had an accuracy of 61.9 [61.6, 62.5], compared with 78.6 [78.4, 79.2] in the DBSI feature set, and 90.5 [90.2, 90.8] in the combined feature set. CONCLUSIONS: When combined with key clinical covariates, preoperative DBSI metrics predicted improvement after surgical decompression for CSM with high accuracy for multiple outcome measures. These results suggest that DBSI may serve as a noninvasive imaging biomarker for CSM valuable in guiding patient selection and informing preoperative counseling. LEVEL OF EVIDENCE: II © 2022 Elsevier Inc.

Author Keywords
Cervical spondylotic myelopathy;  Diffusion basis spectrum imaging;  Diffusion-weighted MRI;  Machine learning;  Support vector machine

Funding details
U01- EY025500
National Institutes of HealthNIHTL1TR002344
National Institute of Neurological Disorders and StrokeNINDSR01 – NS047592
National Center for Advancing Translational SciencesNCATS

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Homo sapiens and Neanderthals share high cerebral cortex integration into adulthood” (2023) Nature Ecology and Evolution

Homo sapiens and Neanderthals share high cerebral cortex integration into adulthood
(2023) Nature Ecology and Evolution, . 

Sansalone, G.a b , Profico, A.c , Wroe, S.a , Allen, K.d , Ledogar, J.e , Ledogar, S.a f , Mitchell, D.R.g , Mondanaro, A.h , Melchionna, M.i , Castiglione, S.i , Serio, C.j , Raia, P.i

a Function, Evolution & Anatomy Research Lab, Zoology Division, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia
b Institute for Marine Biological Resources and Biotechnology (IRBIM), National Research Council, Messina, Italy
c Department of Biology, University of Pisa, Pisa, Italy
d Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
e Department of Health Sciences, East Tennessee State University, Johnson City, TN, United States
f Department of Archaeology & Palaeoanthropology, School of Humanities, University of New England, Armidale, NSW, Australia
g College of Science and Engineering, Flinders University, Adelaide, SA, Australia
h Department of Earth Sciences, Università degli Studi di Firenze, Florence, Italy
i Department of Earth Sciences, Environment and Resources, Università degli Studi di Napoli Federico II, Monte Sant’Angelo, Naples, Italy
j Research Centre in Evolutionary Anthropology and Palaeoecology, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom

Abstract
There is controversy around the mechanisms that guided the change in brain shape during the evolution of modern humans. It has long been held that different cortical areas evolved independently from each other to develop their unique functional specializations. However, some recent studies suggest that high integration between different cortical areas could facilitate the emergence of equally extreme, highly specialized brain functions. Here, we analyse the evolution of brain shape in primates using three-dimensional geometric morphometrics of endocasts. We aim to determine, firstly, whether modern humans present unique developmental patterns of covariation between brain cortical areas; and secondly, whether hominins experienced unusually high rates of evolution in brain covariation as compared to other primates. On the basis of analyses including modern humans and other extant great apes at different developmental stages, we first demonstrate that, unlike our closest living relatives, Homo sapiens retain high levels of covariation between cortical areas into adulthood. Among the other great apes, high levels of covariation are only found in immature individuals. Secondly, at the macro-evolutionary level, our analysis of 400 endocasts, representing 148 extant primate species and 6 fossil hominins, shows that strong covariation between different areas of the brain in H. sapiens and Homo neanderthalensis evolved under distinctly higher evolutionary rates than in any other primate, suggesting that natural selection favoured a greatly integrated brain in both species. These results hold when extinct species are excluded and allometric effects are accounted for. Our findings demonstrate that high covariation in the brain may have played a critical role in the evolution of unique cognitive capacities and complex behaviours in both modern humans and Neanderthals. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Psychedelic Drug Legislative Reform and Legalization in the US” (2023) JAMA Psychiatry

Psychedelic Drug Legislative Reform and Legalization in the US
(2023) JAMA Psychiatry, 80 (1), pp. 77-83. 

Siegel, J.S.a , Daily, J.E.b , Perry, D.A.a , Nicol, G.E.a

a Department of Psychiatry, Washington University in St Louis, St Louis, MO, United States
b Center for Empirical Research in the Law, Washington University in St Louis, St Louis, MO, United States

Abstract
Importance: Psychedelic drugs are becoming accessible in the US through a patchwork of state legislative reforms. This shift necessitates consensus on treatment models, education and guidance for health care professionals, and planning for implementation and regulation. Objective: To assess trends in psychedelics legislative reform and legalization in the US to provide guidance to health care professionals, policy makers, and the public. Evidence Review: Data were compiled from legislative databases (BillTrack50, LexisNexis, and Ballotpedia) from January 1, 2019, to September 28, 2022. Legislation was identified by searching for terms related to psychedelics (eg, psilocybin, MDMA, peyote, mescaline, ibogaine, LSD, ayahuasca, and DMT). Bills were coded by an attorney along 2 axes: which psychedelic drugs would be affected and in what ways (eg, decriminalization, funding for medical research, and right to try). To explore drivers and rates of legislative reform, data were compared with other state indices including 2020 presidential voting margins and marijuana legislative reform. Findings: Twenty-five states have considered 74 bills (69 legislative initiatives, 5 ballot measures); 10 bills were enacted, and 32 were still active. The number of psychedelic reform bills introduced during each calendar year increased steadily from 5 in 2019 to 6 in 2020, 27 in 2021, and 36 in 2022. Nearly all bills specified psilocybin (67 [90%]), and many also included MDMA (3,4-methylenedioxy-methamphetamine; 27 [36%]). While bills varied in their framework, most (43 [58%]) proposed decriminalization, of which few delineated medical oversight (10 of 43 [23%]) or training and/or licensure requirements (15 of 43 [35%]). In general, bills contained less regulatory guidance than the enacted Oregon Measure 109. While early legislative efforts occurred in liberal states, the margin between liberal and conservative states has decreased over time (although the difference was not significant), suggesting that psychedelic drug reform is becoming a bipartisan issue. In addition, an analytic model based on marijuana legalization projected that a majority of states will legalize psychedelics by 2034 to 2037. Conclusions and Relevance: Legislative reform for psychedelic drugs has been proceeding in a rapid, patchwork fashion in the US. Further consideration should be given to key health care issues such as establishing (1) standards for drugs procured outside the medical establishment, (2) licensure criteria for prescribers and therapists, (3) clinical and billing infrastructure, (4) potential contraindications, and (5) use in special populations like youths, older adults, and pregnant individuals.

Document Type: Article
Publication Stage: Final
Source: Scopus

Cognitive and brain reserve predict decline in adverse driving behaviors among cognitively normal older adults” (2022) Frontiers in Psychology

Cognitive and brain reserve predict decline in adverse driving behaviors among cognitively normal older adults
(2022) Frontiers in Psychology, 13, art. no. 1076735, . 

Murphy, S.A.a , Chen, L.b , Doherty, J.M.a , Acharyya, P.a , Riley, N.a , Johnson, A.M.c , Walker, A.a , Domash, H.a , Jorgensen, M.a , Bayat, S.d e , Carr, D.B.f , Ances, B.M.a g h , Babulal, G.M.a i j k

a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
b Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
c Center for Clinical Studies, Washington University School of Medicine, St. Louis, MO, United States
d Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
e Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
f Department of Medicine, Division of Geriatrics and Nutritional Science, Washington University School of Medicine, St. Louis, MO, United States
g Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States
h Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, MO, United States
i Washington University School of Medicine, Institute for Public Health, St. Louis, MO, United States
j Department of Psychology, Faculty of Humanities, University of Johannesburg, Johannesburg, South Africa
k Department of Clinical Research and Leadership, The George Washington University School of Medicine and Health SciencesWashington, WA, United States

Abstract
Daily driving is a multi-faceted, real-world, behavioral measure of cognitive functioning requiring multiple cognitive domains working synergistically to complete this instrumental activity of daily living. As the global population of older adult continues to grow, motor vehicle crashes become more frequent among this demographic. Cognitive reserve (CR) is the brain’s adaptability or functional robustness despite damage, while brain reserve (BR) refers the structural, neuroanatomical resources. This study examined whether CR and BR predicted changes in adverse driving behaviors in cognitively normal older adults. Cognitively normal older adults (Clinical Dementia Rating 0) were enrolled from longitudinal studies at the Knight Alzheimer’s Disease Research Center at Washington University. Participants (n = 186) were ≥65 years of age, required to have Magnetic Resonance Imaging (MRI) data, neuropsychological testing data, and at least one full year of naturalistic driving data prior to the beginning of COVID-19 lockdown in the United States (March 2020) as measured by Driving Real World In-vehicle Evaluation System (DRIVES). Findings suggest numerous changes in driving behaviors over time were predicted by increased hippocampal and whole brain atrophy, as well as lower CR scores as proxied by the Wide Range Achievement Test 4. These changes indicate that those with lower BR and CR are more likely to reduce their driving exposure and limit trips as they age and may be more likely to avoid highways where speeding and aggressive maneuvers frequently occur. Copyright © 2022 Murphy, Chen, Doherty, Acharyya, Riley, Johnson, Walker, Domash, Jorgensen, Bayat, Carr, Ances and Babulal.

Author Keywords
aging;  brain reserve;  cognitive reserve;  driving (veh);  older (elderly) drivers

Funding details
National Institutes of HealthNIH
National Institute on AgingNIAAG056466, AG067428, AG068183
BrightFocus FoundationBFFA2021142S

Document Type: Article
Publication Stage: Final
Source: Scopus

Use of an Interactive Obesity Treatment Approach in Individuals with Severe Mental Illness: Feasibility, Acceptability, and Proposed Engagement Criteria” (2022) JMIR Formative Research

Use of an Interactive Obesity Treatment Approach in Individuals with Severe Mental Illness: Feasibility, Acceptability, and Proposed Engagement Criteria
(2022) JMIR Formative Research, 6 (12), art. no. e38496, . 

Nicol, G.a , Jansen, M.b , Haddad, R.a , Ricchio, A.a , Yingling, M.D.a , Schweiger, J.A.a , Keenoy, K.c , Evanoff, B.A.d , Newcomer, J.W.a

a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
b Division of Child and Adolescent Psychiatry, Department of Psychiatry, Los Angeles David Geffen School of Medicine, University of California, Los Angeles, CA, United States
c Washington University School of Medicine, St. Louis, MO, United States
d Division of General Medical Sciences, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Background: Digital and mobile health interventions are increasingly being used to support healthy lifestyle change, including in certain high-risk populations such as those with severe mental illnesses (SMIs). Life expectancy in this population lags 15 years behind counterparts in the general population, primarily due to obesity-related health conditions. Objective: We tested the feasibility and usability of a 12-week interactive obesity treatment approach (iOTA) to adults with chronic SMIs (depression, bipolar disorder and schizophrenia spectrum disorder) receiving treatment in community settings. The iOTA incorporates short message service (SMS) text messages to supplement monthly in-person health coaching. Methods: Factors hypothesized to be associated with weight change were illness severity and treatment engagement. Severe psychiatric symptoms were defined as baseline Clinical Global Impression severity score of &gt;5. Criterion engagement was defined as a text messaging response rate &gt;80% during the first 4 weeks of treatment. Disordered eating, assessed with the Loss of Control Over Eating Scores, was also evaluated. Participants provided qualitative data, further informing assessment of intervention feasibility, usability, and acceptability. Results: A total of 26 participants were enrolled. The mean age was 48.5 (SD 15.67) years; 40% (10/26) were Black and 60% (15/26) female. Participants with lower symptom severity and adequate engagement demonstrated significantly decreased weight (F1,16=22.54, P&lt;.001). Conversely, high symptom severity and lower text message response rates were associated with trend-level increases in weight (F1,7=4.33, P=.08). Loss-of-control eating was not observed to impact treatment outcome. Participants voiced preference for combination of live health coaching and text messaging, expressing desire for personalized message content. Conclusions: These results demonstrate the feasibility of delivering an adapted iOTA to SMI patients receiving care in community settings and suggest testable criteria for defining sufficient treatment engagement and psychiatric symptom severity, two factors known to impact weight loss outcomes. These important findings suggest specific adaptations may be needed for optimal treatment outcomes in individuals with SMI. ©Ginger Nicol, Madeline Jansen, Rita Haddad, Amanda Ricchio, Michael D Yingling, Julia A Schweiger, Katie Keenoy, Bradley A Evanoff, John W Newcomer.

Author Keywords
health services;  mentally ill people/persons;  mobile health;  obesity

Funding details
P30DK092950
UL1 TR000448
National Institutes of HealthNIH
Centers for Disease Control and PreventionCDC
National Institute of Diabetes and Digestive and Kidney DiseasesNIDDK
Health Resources and Services AdministrationHRSA
Merck
Foundation for Barnes-Jewish HospitalFBJH
Institute of Clinical and Translational SciencesICTSR25 MH112473
McDonnell Center for Systems Neuroscience
Washington University School of Medicine in St. LouisWUSM
Usona Institute

Document Type: Article
Publication Stage: Final
Source: Scopus

Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization” (2022) European Journal of Neuroscience

Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization
(2022) European Journal of Neuroscience, . 

Keane, B.P.a b , Krekelberg, B.c , Mill, R.D.c , Silverstein, S.M.a b d , Thompson, J.L.b e , Serody, M.R.a b , Barch, D.M.f , Cole, M.W.c

a University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
b Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
c Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, NJ, United States
d Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, United States
e Department of Psychiatric Rehabilitation and Counseling Professions, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
f Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Visual shape completion is a canonical perceptual organization process that integrates spatially distributed edge information into unified representations of objects. People with schizophrenia show difficulty in discriminating completed shapes, but the brain networks and functional connections underlying this perceptual difference remain poorly understood. Also unclear is whether brain network differences in schizophrenia occur in related illnesses or vary with illness features transdiagnostically. To address these topics, we scanned (functional magnetic resonance imaging, fMRI) people with schizophrenia, bipolar disorder, or no psychiatric illness during rest and during a task in which they discriminated configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Multivariate pattern differences were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping was used to evaluate the likely involvement of resting-state connections for shape completion. Illusory/fragmented task activation differences (‘modulations’) in the dorsal attention network (DAN) could distinguish people with schizophrenia from the other groups (AUCs >.85) and could transdiagnostically predict cognitive disorganization severity. Activity flow over functional connections from the DAN could predict secondary visual network modulations in each group, except in schizophrenia. The secondary visual network was strongly and similarly modulated in each group. Task modulations were dispersed over more networks in patients compared to controls. In summary, DAN activity during visual perceptual organization is distinct in schizophrenia, symptomatically relevant, and potentially related to improper attention-related feedback into secondary visual areas. © 2022 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Author Keywords
bipolar disorder;  illusory contours;  resting-state functional connectivity;  shape completion;  top-down

Funding details
National Institute of Mental HealthNIMHK01MH108783

Document Type: Article
Publication Stage: Article in Press
Source: Scopus