WashU weekly Neuroscience publications: August 26, 2024

Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling
(2024) npj Digital Medicine, 7 (1), art. no. 216, . 

Holste, G.^a b , Lin, M.^b c , Zhou, R.^d , Wang, F.^a , Liu, L.^d , Yan, Q.^e , Van Tassel, S.H.^f , Kovacs, K.^f , Chew, E.Y.^g , Lu, Z.^h , Wang, Z.^b , Peng, Y.^a

^a Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
^b Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States
^c Department of Surgery, University of Minnesota, Minneapolis, MN, United States
^d Center for Biostatistics and Data Science, Washington University School of Medicine, St. Louis, MO, United States
^e Department of Obstetrics & amp; Gynecology, Columbia University Irving Medical Center, New York, NY, United States
^f Israel Englander Department of Ophthalmology, Weill Cornell Medicine, New York, NY, United States
^g Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health (NIH), Bethesda, MD, United States
^h National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD, United States

Abstract
Deep learning has enabled breakthroughs in automated diagnosis from medical imaging, with many successful applications in ophthalmology. However, standard medical image classification approaches only assess disease presence at the time of acquisition, neglecting the common clinical setting of longitudinal imaging. For slow, progressive eye diseases like age-related macular degeneration (AMD) and primary open-angle glaucoma (POAG), patients undergo repeated imaging over time to track disease progression and forecasting the future risk of developing a disease is critical to properly plan treatment. Our proposed Longitudinal Transformer for Survival Analysis (LTSA) enables dynamic disease prognosis from longitudinal medical imaging, modeling the time to disease from sequences of fundus photography images captured over long, irregular time periods. Using longitudinal imaging data from the Age-Related Eye Disease Study (AREDS) and Ocular Hypertension Treatment Study (OHTS), LTSA significantly outperformed a single-image baseline in 19/20 head-to-head comparisons on late AMD prognosis and 18/20 comparisons on POAG prognosis. A temporal attention analysis also suggested that, while the most recent image is typically the most influential, prior imaging still provides additional prognostic value. © The Author(s) 2024.

Document Type: Article
Publication Stage: Final
Source: Scopus

Parent attitudes towards predictive testing for autism in the first year of life
(2024) Journal of Neurodevelopmental Disorders, 16 (1), art. no. 47, . 

Washington, A.M.^a , Mercer, A.H.^b , Burrows, C.A.^c , Dager, S.R.^d , Elison, J.T.^c , Estes, A.M.^d , Grzadzinski, R.^a , Lee, C.^c , Piven, J.^a , Pruett, J.R., Jr^e , Shen, M.D.^a , Wilfond, B.^d f , Wolff, J.^c , Zwaigenbaum, L.^g , MacDuffie, K.E.^d f

^a University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^b Portland State University, Portland, OR, United States
^c University of Minnesota, Minneapolis, MN, United States
^d University of Washington, Seattle, WA, United States
^e Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^f Seattle Children’s Research Institute, PO Box 5371, M/S JMB-6, Seattle, WA 98145, United States
^g University of Alberta, Edmonton, AB, Canada

Abstract
Background: Emerging biomarker technologies (e.g., MRI, EEG, digital phenotyping, eye-tracking) have potential to move the identification of autism into the first year of life. We investigated the perspectives of parents about the anticipated utility and impact of predicting later autism diagnosis from a biomarker-based test in infancy. Methods: Parents of infants were interviewed to ascertain receptiveness and perspectives on early (6-12 months) prediction of autism using emerging biomarker technologies. One group had experience parenting an older autistic child (n=30), and the other had no prior autism parenting experience (n=25). Parent responses were analyzed using inductive qualitative coding methods. Results: Almost all parents in both groups were interested in predictive testing for autism, with some stating they would seek testing only if concerned about their infant’s development. The primary anticipated advantage of testing was to enable access to earlier intervention. Parents also described the anticipated emotions they would feel in response to test results, actions they might take upon learning their infant was likely to develop autism, attitudes towards predicting a child’s future support needs, and the potential impacts of inaccurate prediction. Conclusion: In qualitative interviews, parents of infants with and without prior autism experience shared their anticipated motivations and concerns about predictive testing for autism in the first year of life. The primary reported motivators for testing—to have more time to prepare and intervene early—could be constrained by familial resources and service availability. Implications for ethical communication of results, equitable early intervention, and future research are discussed. © The Author(s) 2024.

Author Keywords
Autism;  Bioethics;  Biomarkers;  Prediction;  Stakeholder engagement

Document Type: Article
Publication Stage: Final
Source: Scopus

Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair
(2024) Nature Communications, 15 (1), art. no. 6808, . 

Saraswathy, V.M.^a b c , Zhou, L.^a b c , Mokalled, M.H.^a b c

^a Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, United States
^b Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, United States
^c Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, a transient population of injury-responsive neurons (iNeurons) show elevated plasticity 1 week post-injury. We found iNeurons are injury-surviving neurons that acquire a neuroblast-like gene expression signature after injury. CRISPR/Cas9 mutagenesis showed iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair. © The Author(s) 2024.

Document Type: Article
Publication Stage: Final
Source: Scopus

A concentration of visual cortex-like neurons in prefrontal cortex
(2024) Nature Communications, 15 (1), art. no. 7002, . 

Rose, O.^a b , Ponce, C.R.^a

^a Department of Neurobiology, Harvard Medical School, Boston, MA, United States
^b Roy and Diana Vagelos Division of Biology & amp; Biomedical Sciences, Washington University, St. Louis, MO, United States

Abstract
Visual recognition is largely realized through neurons in the ventral stream, though recently, studies have suggested that ventrolateral prefrontal cortex (vlPFC) is also important for visual processing. While it is hypothesized that sensory and cognitive processes are integrated in vlPFC neurons, it is not clear how this mechanism benefits vision, or even if vlPFC neurons have properties essential for computations in visual cortex implemented via recurrence. Here, we investigated if vlPFC neurons in two male monkeys had functions comparable to visual cortex, including receptive fields, image selectivity, and the capacity to synthesize highly activating stimuli using generative networks. We found a subset of vlPFC sites show all properties, suggesting subpopulations of vlPFC neurons encode statistics about the world. Further, these vlPFC sites may be anatomically clustered, consistent with fMRI-identified functional organization. Our findings suggest that stable visual encoding in vlPFC may be a necessary condition for local and brain-wide computations. © The Author(s) 2024.

Document Type: Article
Publication Stage: Final
Source: Scopus

The evaluation of the performance of ChatGPT in the management of labor analgesia
(2024) Journal of Clinical Anesthesia, 98, art. no. 111582, . 

Ismaiel, N.^a , Nguyen, T.P.^b , Guo, N.^b , Carvalho, B.^b , Sultan, P.^b , Chau, A.^c , George, R.^d , Habib, A.^e , Palanisamy, A.^f , Weiniger, C.^g , Wong, C.^h , study collaboratorsⁱ

^a Department of Anesthesiology, El Camino Health, 2500 Grant Road, Mountain View, CA 94040, United States
^b Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Room H3580, MC 5640, Stanford, CA 94305, United States
^c Department of Anesthesiology, Pharmacology & Therapeutics, Faculty of Medicine, University of British Columbia, 11228-11^th Floor, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada
^d Department of Anesthesiology and Pain Medicine, Mount Sinai Hospital, University of Toronto, 600 University Avenue, Room 7-405, Toronto, ON M5G 1X5, Canada
^e Department of Anesthesiology, Duke University Medical Center, 2301 Erwin Road, 5666 Hafs Building, Durham, NC 27710, United States
^f Department of Anesthesiology, Washington University School of Medicine, 1 Barnes- Jewish Hospital Plaza, St. Louis, MO 63110, United States
^g Anesthesiologist, Department of Anesthesiology, Tel Aviv Sourasky Medical Center, Weizmann St 6, Tel Aviv-Yafo, Israel
^h Department of Anesthesiology, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, United States

Abstract
ChatGPT4 is a leading large language model (LLM) chatbot released by OpenAI in 2023. ChatGPT4 can respond to free-text queries, answer questions and make suggestions regarding virtually any topic. ChatGPT4 has successfully answered anesthesia and even obstetric anesthesia knowledge-based questions with reasonable accuracy. However, ChatGPT4 has yet to be challenged in obstetric anesthesia clinical decision-making. Study Objective: In this study, we evaluated the performance of ChatGPT4 in the management of clinical labor analgesia scenarios compared to expert obstetric anesthesiologists. Intervention: Eight clinical questions with progressively increasing medical complexity were posed to ChatGPT4. Measurements: The ChatGPT4 responses were rated by seven expert obstetric anesthesiologists based on safety, accuracy and completeness of each response using a five-point Likert rating scale. Main Results: ChatGPT4 was deemed safe in 73% of responses to the presented obstetric anesthesia clinical scenarios (27% of responses were deemed unsafe). None of the ChatGPT4 responses were unanimously deemed to be safe by all seven expert obstetric anesthesiologists. Moreover, ChatGPT4 responses were overall partly accurate (score 4 out of 5) and somewhat incomplete (score 3.5 out of 5). Conclusions: In summary, approximately one quarter of all responses by ChatGPT4 were deemed unsafe by expert obstetric anesthesiologists. These findings may suggest the need for more fine-tuning and training of LLMs such as ChatGPT4 specifically for clinical decision making in obstetric anesthesia or other specialized medical fields. These LLMs may come to play an important future role in assisting obstetric anesthesiologists in clinical decision making and enhancing overall patient care. © 2024

Author Keywords
Analgesia;  Anesthesiology;  Chatbot;  ChatGPT4;  Obstetric;  Safety

Document Type: Article
Publication Stage: Final
Source: Scopus

Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data
(2024) Journal of Neuroscience Methods, 411, art. no. 110250, . 

Zhang, X.^a , Landsness, E.C.^b , Miao, H.^b , Chen, W.^g , Tang, M.J.^b , Brier, L.M.^c , Culver, J.P.^c d e f , Lee, J.-M.^b c d , Anastasio, M.A.^a

^a Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States
^b Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
^c Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^d Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO 63130, United States
^e Department of Electrical and Systems Engineering, Washington University School of Engineering, St. Louis, MO 63130, United States
^f Department of Physics, Washington University School of Arts and Science, St. Louis, MO 63130, United States
^g Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States

Abstract
Background: Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming, invasive and often suffers from low inter- and intra-rater reliability. Therefore, an automated sleep state classification method that operates on spatiotemporal WFCI data is desired. New method: A hybrid network architecture consisting of a convolutional neural network (CNN) to extract spatial features of image frames and a bidirectional long short-term memory network (BiLSTM) with attention mechanism to identify temporal dependencies among different time points was proposed to classify WFCI data into states of wakefulness, NREM and REM sleep. Results: Sleep states were classified with an accuracy of 84 % and Cohen’s κ of 0.64. Gradient-weighted class activation maps revealed that the frontal region of the cortex carries more importance when classifying WFCI data into NREM sleep while posterior area contributes most to the identification of wakefulness. The attention scores indicated that the proposed network focuses on short- and long-range temporal dependency in a state-specific manner. Comparison with existing method: On a held out, repeated 3-hour WFCI recording, the CNN-BiLSTM achieved a κ of 0.67, comparable to a κ of 0.65 corresponding to the human EEG/EMG-based scoring. Conclusions: The CNN-BiLSTM effectively classifies sleep states from spatiotemporal WFCI data and will enable broader application of WFCI in sleep research. © 2024 The Authors

Author Keywords
Automated sleep state classification;  CNN-BiLSTM;  Deep learning;  Local sleep;  Wide-field calcium imaging

Document Type: Article
Publication Stage: Final
Source: Scopus

Multi-site EEG studies in early infancy: Methods to enhance data quality
(2024) Developmental Cognitive Neuroscience, 69, art. no. 101425, . 

Dickinson, A.^a , Booth, M.^b , Daniel, M.^a , Campbell, A.^c , Miller, N.^d , Lau, B.^e , Zempel, J.^f , Webb, S.J.^g , Elison, J.^h , Lee, A.K.C.ⁱ , Estes, A.ⁱ , Dager, S.^j , Hazlett, H.^c , Wolff, J.^d , Schultz, R.^k , Marrus, N.^f , Evans, A.^l , Piven, J.^c , Pruett, J.R., Jr.^f , Jeste, S.^b m , for the IBIS Networkⁿ

^a Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, CA, United States
^b Department of Neurology, Children’s Hospital of Los Angeles, Los Angeles, CA, United States
^c Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^d Center for Neurobehavioral Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, United States
^e Department of Otolaryngology – Head and Neck Surgery, University of Washington, Seattle, WA, United States
^f Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^g Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
^h Institute of Child Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, United States
ⁱ Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
^j Department of Radiology, University of Washington, Seattle, WA, United States
^k Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^l McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
^m Department of Pediatrics and Neurology, University of Southern California, Los Angeles, CA, United States

Abstract
Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors. © 2024 The Authors

Author Keywords
Autism;  Early identification;  Electrophysiology;  Multi-site;  Multimodal

Document Type: Article
Publication Stage: Final
Source: Scopus

Longitudinal associations between five factor model and impulsive personality traits and PTSD symptoms: Findings from the AURORA study
(2024) Journal of Research in Personality, 112, art. no. 104524, . 

Hyatt, C.S.^a b , Reddi, P.J.^c , Sharpe, B.M.^d , Michopoulos, V.^a e , van Rooij, S.J.H.^a , House, S.L.^f , Beaudoin, F.L.^g h , An, X.ⁱ , Stevens, J.S.^a , Zeng, D.^j , Neylan, T.C.^k , Clifford, G.D.^l m , Linnstaedt, S.D.ⁱ , Germine, L.T.^n o p , Bollen, K.A.^q , Rauch, S.L.^n p r , Haran, J.P.^s , Lewandowski, C.^t , Musey, P.I.^u , Hendry, P.L.^v , Sheikh, S.^v , Jones, C.W.^w , Punches, B.E.^x y , Kurz, M.C.^z aa ab , Swor, R.A.^ac , Hudak, L.A.^ad , Pascual, J.L.^ae af , Seamon, M.J.^af ag , Harris, E.^ah , Pearson, C.^ai , Peak, D.A.^aj , Merchant, R.C.^ak , Domeier, R.M.^al , Rathlev, N.K.^am , Sergot, P.^an , Sanchez, L.D.^ak ao , Bruce, S.E.^ap , Miller, M.W.^aq ar , Pietrzak, R.H.^as at , Joormann, J.^au , Pizzagalli, D.A.^p av , Sheridan, J.F.^aw ax , Smoller, J.W.^ay az , Harte, S.E.^ba bb , Elliott, J.M.^bc bd be , McLean, S.A.^bf bg , Kessler, R.C.^bh , Ressler, K.J.^p av , Koenen, K.C.^bi , Maples-Keller, J.L.^a

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

Abstract
We used data from the Advancing Understanding of Recovery after Trauma (AURORA) study to investigate prospective links between five factor model and impulsive personality traits and PTSD symptoms at baseline (N = 2943), three-months post-trauma (N = 2400), and one-year post-trauma (N = 1591) in individuals recruited from emergency departments within 72 h of trauma exposure. Neuroticism and Negative Urgency bore the largest relations (rs > 0.30) to nearly all individual PTSD symptoms and symptom total at all time points. Neuroticism was an incremental predictor of every PTSD symptom at each time point. Low Agreeableness and low Conscientiousness were incremental predictors of several PTSD symptoms. These findings highlight personality assessment as an efficient, effective screening tool for PTSD risk. © 2024

Author Keywords
Five Factor Model;  Impulsivity;  Negative Urgency;  Neuroticism;  Personality traits;  Posttraumatic stress disorder;  Stress;  Trauma;  Trauma exposure;  UPPS model

Document Type: Article
Publication Stage: Final
Source: Scopus

Mice lacking Astn2 have ASD-like behaviors and altered cerebellar circuit properties
(2024) Proceedings of the National Academy of Sciences of the United States of America, 121 (34), pp. e2405901121. 

Hanzel, M.^a , Fernando, K.^b , Maloney, S.E.^c , Horn, Z.^a d , Gong, S.^e , Mätlik, K.^a , Zhao, J.^a , Pasolli, H.A.^f , Heissel, S.^g , Dougherty, J.D.^c h , Hull, C.^b , Hatten, M.E.^a

^a Laboratory of Developmental Neurobiology, Rockefeller University, NY, NY 10065, United States
^b Neurobiology Department, Duke University, Durham, United Kingdom
^c Department of Psychiatry and the Intellectual and Developmental Disabilities Research Center, Washington University Medical School, St. Louis, MO 63130, United States
^d InVitro Cell Research LLC, Englewood, United States
^e Helen and Robert Appel Alzheimer’s Disease Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, NY, NY 10021, United States
^f Electron Microscopy Resource Center, Rockefeller University, NY, NY 10065, United States
^g Proteomics Resource Center, Rockefeller University, NY, NY 10065, United States
^h Department of Genetics, Washington University Medical School, St. Louis, MO 63130, United States

Abstract
Astrotactin 2 (ASTN2) is a transmembrane neuronal protein highly expressed in the cerebellum that functions in receptor trafficking and modulates cerebellar Purkinje cell (PC) synaptic activity. Individuals with ASTN2 mutations exhibit neurodevelopmental disorders, including autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), learning difficulties, and language delay. To provide a genetic model for the role of the cerebellum in ASD-related behaviors and study the role of ASTN2 in cerebellar circuit function, we generated global and PC-specific conditional Astn2 knockout (KO and cKO, respectively) mouse lines. Astn2 KO mice exhibit strong ASD-related behavioral phenotypes, including a marked decrease in separation-induced pup ultrasonic vocalization calls, hyperactivity, repetitive behaviors, altered behavior in the three-chamber test, and impaired cerebellar-dependent eyeblink conditioning. Hyperactivity and repetitive behaviors are also prominent in Astn2 cKO animals, but they do not show altered behavior in the three-chamber test. By Golgi staining, Astn2 KO PCs have region-specific changes in dendritic spine density and filopodia numbers. Proteomic analysis of Astn2 KO cerebellum reveals a marked upregulation of ASTN2 family member, ASTN1, a neuron-glial adhesion protein. Immunohistochemistry and electron microscopy demonstrate a significant increase in Bergmann glia volume in the molecular layer of Astn2 KO animals. Electrophysiological experiments indicate a reduced frequency of spontaneous excitatory postsynaptic currents (EPSCs), as well as increased amplitudes of both spontaneous EPSCs and inhibitory postsynaptic currents in the Astn2 KO animals, suggesting that pre- and postsynaptic components of synaptic transmission are altered. Thus, ASTN2 regulates ASD-like behaviors and cerebellar circuit properties.

Author Keywords
ASTN2;  autism spectrum disorder;  cerebellum;  neurodevelopmental disorder;  Purkinje cell

Document Type: Article
Publication Stage: Final
Source: Scopus

ECOG-ACRIN EAZ171: Prospective Validation Trial of Germline Predictors of Taxane-Induced Peripheral Neuropathy in Black Women With Early-Stage Breast Cancer
(2024) Journal of Clinical Oncology, 42 (24), pp. 2899-2907. 

Schneider, B.P.^a , Zhao, F.^b , Ballinger, T.J.^a , Garcia, S.F.^c , Shen, F.^a , Virani, S.^d , Cella, D.^c , Bales, C.^a , Jiang, G.^a , Hayes, L.^e , Miller, N.^e , Srinivasiah, J.^f , Stringer-Reasor, E.M.^g , Chitalia, A.^h , Davis, A.A.ⁱ , Makower, D.F.^j , Incorvati, J.^k , Simon, M.A.^c , Mitchell, E.P.^l q , Demichele, A.^m , Miller, K.D.^a , Sparano, J.A.ⁿ , Wagner, L.I.^o , Wolff, A.C.^p

^a Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United States
^b Dana Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, MA, United States
^c Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, United States
^d Aurora Cancer Care-Southern Lakes Vlcc, Burlington, WI, United States
^e Pink-4-Ever Ending Disparities, Indianapolis, IN, United States
^f Georgia Ncorp, Decatur, GA, United States
^g University of Alabama, Birmingham o’Neal Comprehensive Cancer Center, Birmingham, AL, United States
^h MedStar Washington Hospital Center, Washington, DC, United States
ⁱ Washington University School of Medicine, St Louis, MO, United States
^j Montefiore Medical Center-Weiler Hospital, New York, NY, United States
^k Fox Chase Comprehensive Cancer Center, Philadelphia, PA, United States
^l Thomas Jefferson University Hospital, Philadelphia, PA, United States
^m University of Pennsylvania, Philadelphia, PA, United States
ⁿ Icahn School of Medicine at Mount Sinai, Tisch Cancer Institute, New York, NY, United States
^o University of North Carolina, Chapel Hill, NC, United States
^p Johns Hopkins University/Sidney Kimmel Comprehensive Cancer Center, Australia
^q Baltimore, MD, United States

Abstract
PURPOSEBlack women experience higher rates of taxane-induced peripheral neuropathy (TIPN) compared with White women when receiving adjuvant once weekly paclitaxel for early-stage breast cancer, leading to more dose reductions and higher recurrence rates. EAZ171 aimed to prospectively validate germline predictors of TIPN and compare rates of TIPN and dose reductions in Black women receiving (neo)adjuvant once weekly paclitaxel and once every 3 weeks docetaxel for early-stage breast cancer.METHODSWomen with early-stage breast cancer who self-identified as Black and had intended to receive (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel were eligible, with planned accrual to 120 patients in each arm. Genotyping was performed to determine germline neuropathy risk. Grade 2-4 TIPN by Common Terminology Criteria for Adverse Events (CTCAE) v5.0 was compared between high- versus low-risk genotypes and between once weekly paclitaxel versus once every 3 weeks docetaxel within 1 year. Patient-rated TIPN and patient-reported outcomes were compared using patient-reported outcome (PRO)-CTCAE and Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity.RESULTSTwo hundred and forty of 249 enrolled patients had genotype data, and 91 of 117 (77.8%) receiving once weekly paclitaxel and 87 of 118 (73.7%) receiving once every 3 weeks docetaxel were classified as high-risk. Physician-reported grade 2-4 TIPN was not significantly different in high- versus low-risk genotype groups with once weekly paclitaxel (47% v 35%; P =.27) or with once every 3 weeks docetaxel (28% v 19%; P =.47). Grade 2-4 TIPN was significantly higher in the once weekly paclitaxel versus once every 3 weeks docetaxel arm by both physician-rated CTCAE (45% v 29%; P =.02) and PRO-CTCAE (40% v 24%; P =.03). Patients receiving once weekly paclitaxel required more dose reductions because of TIPN (28% v 9%; P <.001) or any cause (39% v 25%; P =.02).CONCLUSIONGermline variation did not predict risk of TIPN in Black women receiving (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel. Once weekly paclitaxel was associated with significantly more grade 2-4 TIPN and required more dose reductions than once every 3 weeks docetaxel. © American Society of Clinical Oncology.

Document Type: Article
Publication Stage: Final
Source: Scopus

An Accurate and Rapidly Calibrating Speech Neuroprosthesis
(2024) The New England Journal of Medicine, 391 (7), pp. 609-618. 

Card, N.S., Wairagkar, M., Iacobacci, C., Hou, X., Singer-Clark, T., Willett, F.R., Kunz, E.M., Fan, C., Vahdati Nia, M., Deo, D.R., Srinivasan, A., Choi, E.Y., Glasser, M.F., Hochberg, L.R., Henderson, J.M., Shahlaie, K., Stavisky, S.D., Brandman, D.M.

From the Departments of Neurological Surgery (N.S.C., M.W., C.I., X.H., T.S.-C., M.V.N., A.S., K.S., S.D.S., D.M.B.), Computer Science (X.H., M.V.N.), and Biomedical Engineering (T.S.-C., A.S.), University of California, Davis, Davis, and the Departments of Neurosurgery (D.R.D., E.Y.C., J.M.H.), Electrical Engineering (E.M.K.), and Computer Science (C.F.), the Wu Tsai Neurosciences Institute (E.M.K., J.M.H.), the Howard Hughes Medical Institute (F.R.W.), and Bio-X (J.M.H.), Stanford University, Stanford – both in California; the Departments of Radiology and Neuroscience, Washington University School of Medicine, Saint Louis (M.F.G.); the School of Engineering and Carney Institute for Brain Sciences, Brown University (L.R.H.), and the Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs Office of Rehabilitation Research and Development, VA Providence Healthcare (L.R.H.) – both in Providence, RI; and the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.R.H.)

Abstract
BACKGROUND: Brain-computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain-computer interfaces has been restricted by extensive training requirements and limited accuracy. METHODS: A 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice. RESULTS: On the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours. CONCLUSIONS: In a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.). Copyright © 2024 Massachusetts Medical Society.

Document Type: Article
Publication Stage: Final
Source: Scopus

Neuronal Activity in the Gustatory Cortex during Economic Choice
(2024) Journal of Neuroscience, 44 (33), art. no. e2150232024, . 

Jezzini, A.^a , Padoa-Schioppa, C.^a b c

^a Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, United States
^b Department of Economics, Washington University in St. Louis, St. Louis, MO 63110, United States
^c Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, United States

Abstract
An economic choice entails computing and comparing the values of individual offers. Offer values are represented in the orbitofrontal cortex (OFC)—an area that participates in value comparison—but it is unknown where offer values are computed in the first place. One possibility is that this computation takes place in OFC. Alternatively, offer values might be computed upstream of OFC. For choices between edible goods, a primary candidate is the gustatory region of the anterior insula (gustatory cortex, GC). Here we recorded from the GC of male rhesus monkeys choosing between different juice types. As a population, neurons in GC represented the flavor, the quantity, and the subjective value of the juice chosen by the animal. These variables were represented by distinct groups of cells and with different time courses. Specifically, chosen value signals emerged shortly after offer presentation, while neurons encoding the chosen juice and the chosen quantity peaked after juice delivery. Surprisingly, neurons in GC did not represent individual offer values in a systematic way. In a computational sense, the variables encoded in GC follow the process of value comparison. Thus our results argue against the hypothesis that offer values are computed in GC. At the same time, signals representing the subjective value of the expected reward indicate that responses in GC are not purely sensory. Thus neuronal responses in GC appear consummatory in nature. Copyright © 2024 the authors.

Author Keywords
decision making;  gustatory cortex;  neurophysiology;  nonhuman primates;  subjective value

Document Type: Article
Publication Stage: Final
Source: Scopus

Disruption of the nascent polypeptide-associated complex leads to reduced polyglutamine aggregation and toxicity
(2024) PLoS ONE, 19 (8 AUGUST), art. no. e0303008, . 

Dublin-Ryan, L.B., Bhadra, A.K., True, H.L.

Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, United States

Abstract
The nascent polypeptide-associate complex (NAC) is a heterodimeric chaperone complex that binds near the ribosome exit tunnel and is the first point of chaperone contact for newly synthesized proteins. Deletion of the NAC induces embryonic lethality in many multi-cellular organisms. Previous work has shown that the deletion of the NAC rescues cells from prion-induced cytotoxicity. This counterintuitive result led us to hypothesize that NAC disruption would improve viability in cells expressing human misfolding proteins. Here, we show that NAC disruption improves viability in cells expressing expanded polyglutamine and also leads to delayed and reduced aggregation of expanded polyglutamine and changes in polyglutamine aggregate morphology. Moreover, we show that NAC disruption leads to changes in de novo yeast prion induction. These results indicate that the NAC plays a critical role in aggregate organization as a potential therapeutic target in neurodegenerative disorders. © 2024 Dublin-Ryan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Document Type: Article
Publication Stage: Final
Source: Scopus

Posttraumatic Stress Disorder and Type 2 Diabetes Outcomes in Veterans
(2024) JAMA Network Open, 7 (8), p. e2427569. 

Scherrer, J.F.^a b c d , Salas, J.^c d , Wang, W.^a , Freedland, K.E.^e , Lustman, P.J.^e , Schnurr, P.P.^f g , Cohen, B.E.^h i , Jaffe, A.S.^j k , Friedman, M.J.^g

^a Department of Family and Community Medicine, Saint Louis University School of Medicine, St Louis, MO, United States
^b Department of Psychiatry and Behavioral Neuroscience, Saint Louis University School of Medicine, St Louis, MO, United States
^c Advanced Health Data Research Institute, Saint Louis University School of Medicine, St Louis, MO, United States
^d Harry S. Truman Memorial Veterans’ Hospital, Columbia, MO, United States
^e Department of Psychiatry, Washington University School of Medicine, St Louis, MO, United States
^f National Center for PTSD, White River JunctionVT, United States
^g Department of Psychiatry, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
^h Department of Medicine, University of California San Francisco School of Medicine, San Francisco, Mexico
ⁱ San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States
^j Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
^k Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States

Abstract
Importance: Posttraumatic stress disorder (PTSD) symptom reduction is linked with lower risk of incident type 2 diabetes (T2D), but little is known about the association between PTSD and comorbid T2D outcomes. Whether PTSD is a modifiable risk factor for adverse T2D outcomes is unknown. Objective: To determine whether patients with PTSD who improved and no longer met diagnostic criteria for PTSD had a lower risk of adverse T2D outcomes compared with patients with persistent PTSD. Design, Setting, and Participants: This retrospective cohort study used deidentified data from US Veterans Health Administration (VHA) historical medical records (from October 1, 2011, to September 30, 2022) to create a cohort of patients aged 18 to 80 years with comorbid PTSD and T2D. Data analysis was performed from March 1 to June 1, 2024. Exposures: Diagnoses of PTSD and T2D. Main Outcomes and Measures: The main outcomes were insulin initiation, poor glycemic control, any microvascular complication, and all-cause mortality. Improvement of PTSD was defined as no longer meeting PTSD diagnostic criteria, per a PTSD Checklist score of less than 33. Entropy balancing controlled for confounding. Survival and competing risk models estimated the association between meeting PTSD criteria and T2D outcomes. Subgroup analyses examined variation by age, sex, race, PTSD severity, and comorbid depression status. Results: The study cohort included 10 002 veterans. More than half of patients (65.3%) were aged older than 50 years and most (87.2%) were men. Patients identified as Black (31.6%), White (62.7%), or other race (5.7%). Before controlling for confounding with entropy balancing, patients who no longer met PTSD diagnostic criteria had similar incidence rates for starting insulin (22.4 vs 24.4 per 1000 person-years), poor glycemic control (137.1 vs 133.7 per 1000 person-years), any microvascular complication (108.4 vs 104.8 per 1000 person-years), and all-cause mortality (11.2 vs 11.0 per 1000 person-years) compared with patients with persistent PTSD. After controlling for confounding, no longer meeting PTSD criteria was associated with a lower risk of microvascular complications (hazard ratio [HR], 0.92 [95% CI, 0.85-0.99]). Among veterans aged 18 to 49 years, no longer meeting PTSD criteria was associated with a lower risk of insulin initiation (HR, 0.69 [95% CI, 0.53-0.88]) and all-cause mortality (HR, 0.39 [95% CI, 0.19-0.83]). Among patients without depression, no longer meeting PTSD criteria was associated with a lower risk of insulin initiation (HR, 0.73 [95% CI, 0.55-0.97]). Conclusions and Relevance: The findings of this cohort study of patients with comorbid PTSD and T2D suggest that PTSD is a modifiable risk factor associated with a modest reduction in microvascular complications. Further research is needed to determine whether findings are similar in non-VHA health care settings.

Document Type: Article
Publication Stage: Final
Source: Scopus

The headache research priorities: Research goals from the American Headache Society and an international multistakeholder expert group
(2024) Headache, . 

Schwedt, T.J.^a , Pradhan, A.A.^b , Oshinsky, M.L.^c , Brin, M.F.^d e , Rosen, H.^f , Lalvani, N.^g , Charles, A.^h , Ashina, M.ⁱ , Do, T.P.ⁱ , Burstein, R.^j k , Gelfand, A.A.^l , Dodick, D.W.^a m , Pozo-Rosich, P.ⁿ , Lipton, R.B.^o , Ailani, J.^p , Szperka, C.L.^q , Charleston, L., IV^r , Digre, K.B.^s , Russo, A.F.^t , Buse, D.C.^o u , Powers, S.W.^v w , Tassorelli, C.^x y , Goadsby, P.J.^h z , Ashina, M.^aa , Brin, M.F.^aa , Chong, C.D.^aa , De Icco, R.^aa , Do, T.P.^aa , Hay, D.^aa , Karsan, N.^aa , Magis, D.^aa , van Oosterhout, R.^aa , Wang, S.-J.^aa , Winsvold, B.^aa , Charles, A.^aa , Dussor, G.^aa , Holland, P.^aa , Tolner, E.^aa , Sinclair, A.^aa , Johnson, K.^aa , Renthal, W.^aa , Burstein, R.^aa , Gelfand, A.A.^aa , Akerman, S.^aa , Brennan, K.C.^aa , Buzby, M.^aa , Harriott, A.^aa , Jensen, R.^aa , van den Maagdenberg, A.^aa , May, A.^aa , MacGregor, A.^aa , Robertson, C.^aa , Dodick, D.W.^aa , Pozo-Rosich, P.^aa , Aurora, S.^aa , Cady, R.^aa , Diener, H.C.^aa , Gil-Gouveia, R.^aa , Griffiths, L.^aa , Lalvani, N.^aa , Lay, C.^aa , Lee, M.J.^aa , Leroux, E.^aa , Lisicki, M.^aa , Pascual, J.^aa , Peres, M.^aa , Ailani, J.^aa , Lipton, R.B.^aa , Armand, C.^aa , Burish, M.^aa , Dabruzzo, B.^aa , Ezzati, A.^aa , Morton, B.^aa , Newman, L.^aa , Ozge, A.^aa , Smitherman, T.^aa , Starling, A.^aa , Wirth, R.J.^aa , Larry Charleston, I.V.^aa , Szperka, C.L.^aa , O’Brien, H.^aa , Peres, M.^aa , Sanders, J.^aa , Vargas, B.^aa , Wells, R.E.^aa , Digre, K.B.^aa , Russo, A.F.^aa , Ahn, A.^aa , Burton, M.^aa , Galetta, S.^aa , Glaser, C.^aa , Godley, F.^aa , Heinricher, M.^aa , Hershey, A.^aa , Oshinsky, M.L.^aa , Recober, A.^aa , Robbins, M.^aa , Tietjen, G.^aa , Buse, D.C.^aa , Powers, S.W.^aa , Kempner, J.^aa , Kessel, S.^aa , Law, E.^aa , McGinley, J.^aa , Minen, M.^aa , Ross, A.^aa , Seng, E.^aa , Shapiro, R.^aa , the Headache Research Priorities Working Group Members^aa

^a Mayo Clinic, Phoenix, AZ, United States
^b Washington University School of Medicine, St. Louis, MO, United States
^c National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States
^d AbbVie, Irvine, CA, United States
^e Department of Neurology, University of California Irvine, Irvine, CA, United States
^f American Headache Society, Mount Royal, NJ, United States
^g American Migraine Foundation, New York, NY, United States
^h University of California Los Angeles, Los Angeles, CA, United States
ⁱ Department of Neurology, Danish Headache Center, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
^j Department of Anesthesia, Harvard Medical School, Boston, MA, United States
^k Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
^l Child & Adolescent Headache Program, University of California San Francisco, San Francisco, CA, United States
^m Atria Academy of Science and Medicine, New York, NY, United States
ⁿ Hospital Universitari Vall d’Hebron, Barcelona, Spain
^o Albert Einstein College of Medicine, Bronx, NY, United States
^p Georgetown University Hospital, Washington, DC, United States
^q Perelman School of Medicine at the University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^r Michigan State University College of Human Medicine, East Lansing, MI, United States
^s University of Utah, Salt Lake City, UT, United States
^t University of Iowa, Iowa City, IA, United States
^u Vector Psychometric Group, Chapel Hill, NC, United States
^v Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
^w Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children’s Hospital, Cincinnati, OH, United States
^x University of Pavia, Pavia, Italy
^y IRCCS Mondino Foundation, Pavia, Italy
^z NIHR King’s Clinical Research Facility, King’s College London, London, United Kingdom

Abstract
Objective: To identify and disseminate research priorities for the headache field that should be areas of research focus during the next 10 years. Background: Establishing research priorities helps focus and synergize the work of headache investigators, allowing them to reach the most important research goals more efficiently and completely. Methods: The Headache Research Priorities organizing and executive committees and working group chairs led a multistakeholder and international group of experts to develop headache research priorities. The research priorities were developed and reviewed by clinicians, scientists, people with headache, representatives from headache organizations, health-care industry representatives, and the public. Priorities were revised and finalized after receiving feedback from members of the research priorities working groups and after a public comment period. Results: Twenty-five research priorities across eight categories were identified: human models, animal models, pathophysiology, diagnosis and management, treatment, inequities and disparities, research workforce development, and quality of life. The priorities address research models and methods, development and optimization of outcome measures and endpoints, pain and non-pain symptoms of primary and secondary headaches, investigations into mechanisms underlying headache attacks and chronification of headache disorders, treatment optimization, research workforce recruitment, development, expansion, and support, and inequities and disparities in the headache field. The priorities are focused enough that they help to guide headache research and broad enough that they are widely applicable to multiple headache types and various research methods. Conclusions: These research priorities serve as guidance for headache investigators when planning their research studies and as benchmarks by which the headache field can measure its progress over time. These priorities will need updating as research goals are met and new priorities arise. © 2024 American Headache Society.

Author Keywords
diagnosis;  disparities;  migraine;  pathophysiology;  quality of life;  treatment

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

What predicts the initiation and outcomes of interpersonal emotion regulation in everyday life?
(2024) Motivation and Emotion, . 

Thompson, R.J.^a , Liu, D.Y.^b , Lai, J.^a

^a Department of Psychological and Brain Sciences, Washington University in St. Louis, 1 Brookings Drive; CB 1125, St. Louis, MO 63130, United States
^b Department of Psychology, University of Denver, Denver, United States

Abstract
Research examining initiation and outcomes of ER has primarily examined when people regulate their own emotions. In the present study, we investigated what predicts the initiation and outcomes of interpersonal emotion regulation (IER). We also examined whether the associations varied by major depressive disorder (MDD), which is characterized by several emotion regulation challenges, including in IER. Adults with and without MDD (N = 215) completed a 14-day EMA protocol, reporting on their emotional experience, recent events, and recent IER interactions. For IER initiation, we examined two features of subjective emotional experiences: participants’ affect (negative affect, positive affect) and emotional awareness (attention to emotion, emotional clarity), and two situational characteristics: event unpleasantness and goal interruption. For IER outcomes, we focused on sharing partners’ characteristics. Analyses utilized multilevel modeling. We focus on reporting within-person findings. Participants were more likely to initiate IER when the situation was more unpleasant and when goals were interrupted. Regarding IER outcomes, the extent to which participants experienced improved feelings about the problem and relational closeness varied depending on who was the sharing partner. Additionally, perceived warmth of sharing partner was associated with better IER outcomes. Initiating IER did not differ by MDD status, whereas associations between perceived warmth and IER outcomes did. Findings elucidate factors relevant to the IER process and serve to provide important insight into the contexts in which individuals might seek others to support their regulation and when the sharing partner were the most helpful in IER. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

Author Keywords
Ecological momentary assessment;  Experience sampling;  Interpersonal emotion regulation;  Intrinsic emotion regulation;  Major depressive disorder;  Social sharing

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

Comparing balance using the BESTest in Alzheimer, Huntington and Parkinson disease
(2024) Neurodegenerative Disease Management, . 

Tueth, L.E.^a , Duncan, R.P.^a b , Crowner, B.E.^a b , Earhart, G.M.^a b c

^a Washington University in St. Louis School of Medicine, Program in Physical Therapy, St. Louis, MO 63108, United States
^b Washington University in St. Louis School of Medicine, Department of Neurology, St. Louis, MO 63108, United States
^c Washington University in St. Louis School of Medicine, Department of Neuroscience, St. Louis, MO 63108, United States

Abstract
Aim: Individuals with Alzheimer disease (AD), Huntington disease (HD) and Parkinson disease (PD) have impaired balance, and comparing these deficits could improve management of neurological diseases. Methods: Scores on the Balance Evaluation Systems Test (BESTest) were compared across three groups, consisting of individuals with AD, HD and PD in early stages of their respective disease. Results: Individuals with PD had significantly higher scores on the BESTest than individuals with AD (95% CI [4.30, 21.37], p < 0.01) or HD (95% CI [6.53, 24.18], p < 0.001). Individuals with AD and HD were not significantly different on the overall BESTest or any of its subsections. Conclusion: AD and HD may have overlapping pathologies resulting in early and similar balance impairments in these groups. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Author Keywords
alzheimer disease;  balance;  cognitive impairment;  huntington disease;  parkinson disease

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

A Pilot Feasibility Trial of Mind–Body Tactical Training for Firefighters: Evaluation of a Yoga-Based Transdiagnostic Program
(2024) Mindfulness, . 

Weathers-Meyer, A.J.^a b , Lowe, A.C.^a c , McGrew, S.J.^d , Sutherland, N.E.^a e , Yann, C.M.G.^f , Beyl, R.A.^c , Vujanovic, A.A.^d

^a Louisiana State University, Baton Rouge, LA, United States
^b St. George Fire Protection District, Baton Rouge, LA, United States
^c Pennington Biomedical Research Center, Baton Rouge, LA, United States
^d University of Houston, Houston, TX, United States
^e Chatham University, Pittsburgh, PA, United States
^f Washington University in St. Louis, St. Louis, MO, United States

Abstract
Objectives: Firefighters are at heightened risk for chronic occupational stress and exposure to potentially traumatic events. Experiencing potentially traumatic events is a risk factor for various psychiatric symptoms among firefighters, notably posttraumatic stress disorder (PTSD), depression, and anxiety. This study evaluated the feasibility and preliminary effectiveness of yoga to reduce PTSD symptoms, negative affect, and trait anxiety in firefighters. Methods: A total of 108 trauma-exposed career firefighters (99% male; Mage = 34.55, SD = 8.37) were enrolled in a single-arm 8-week yoga intervention, termed Mind–Body Tactical Training (MBTT). Feasibility was assessed in five domains. Self-report measures were used to evaluate the MBTT intervention’s effectiveness in reducing symptoms of PTSD, negative affect, and trait anxiety. The Intervention Appropriateness Measure was employed to assess acceptability. Attrition, attendance, and intervention costs were used to determine demand, implementation, and practicality, respectively. Results: Total PTSD (p &lt; 0.001, d = 0.426), negative affect (p = 0.029, d = 0.242), and trait anxiety (p &lt; 0.001, d = 0.327) decreased from pre- to post-intervention. Improvements in trait anxiety were also observed from pre-intervention to follow-up (p = 0.032). The intervention was generally acceptable to participants, had a 6.48% attrition rate, and had an 80.73 ± 18.96% class attendance. The cost of instructors and equipment totaled US$6636.78, equating to a cost per participant per attended class of US$4.76. Conclusions: The current study provides initial evidence for the feasibility and effectiveness of yoga as a transdiagnostic treatment for firefighters. Preregistration: This study is not preregistered. © The Author(s) 2024.

Author Keywords
Anxiety;  Depression;  Firefighter;  First responder;  Intervention;  Mindfulness;  Mind–body;  PTSD;  Trauma;  Yoga

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

Brain aging patterns in a large and diverse cohort of 49,482 individuals
(2024) Nature Medicine, . 

Yang, Z.^a b c , Wen, J.^d , Erus, G.^a , Govindarajan, S.T.^a , Melhem, R.^a , Mamourian, E.^a , Cui, Y.^a , Srinivasan, D.^a , Abdulkadir, A.^e , Parmpi, P.^a , Wittfeld, K.^f , Grabe, H.J.^f g , Bülow, R.^h , Frenzel, S.^f , Tosun, D.ⁱ , Bilgel, M.^j , An, Y.^j , Yi, D.^k , Marcus, D.S.^l , LaMontagne, P.^l , Benzinger, T.L.S.^l , Heckbert, S.R.^m , Austin, T.R.^m , Waldstein, S.R.ⁿ , Evans, M.K.^o , Zonderman, A.B.^o , Launer, L.J.^p , Sotiras, A.^q , Espeland, M.A.^r , Masters, C.L.^s , Maruff, P.^s , Fripp, J.^t , Toga, A.W.^u , O’Bryant, S.^v , Chakravarty, M.M.^w , Villeneuve, S.^x , Johnson, S.C.^y , Morris, J.C.^z , Albert, M.S.^aa , Yaffe, K.^ab , Völzke, H.^ac , Ferrucci, L.^ad , Nick Bryan, R.^ae , Shinohara, R.T.^a af , Fan, Y.^a , Habes, M.^ag , Lalousis, P.A.^ah , Koutsouleris, N.^ah ai , Wolk, D.A.^aj , Resnick, S.M.^j , Shou, H.^a af , Nasrallah, I.M.^a ae , Davatzikos, C.^a

^a Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^b Graduate Group in Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, PA, United States
^c GE Healthcare, Bellevue, WA, United States
^d Laboratory of AI and Biomedical Science (LABS), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
^e Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
^f Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
^g Site Rostock/Greifswald, German Center for Neurodegenerative Diseases (DZNE), Greifswald, Germany
^h Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
ⁱ Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
^j Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
^k Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, South Korea
^l Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
^m Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, United States
ⁿ Department of Psychology, University of Maryland, Baltimore County, Baltimore, MD, United States
^o Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, United States
^p Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, MD, United States
^q Department of Radiology and Institute for Informatics, Data Science & amp; Biostatistics, Washington University in St. Louis, St. Louis, MO, United States
^r Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States
^s Florey Institute, The University of Melbourne, Parkville, VIC, Australia
^t CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, QLD, Australia
^u Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
^v Institute for Translational Research University of North Texas Health Science Center, Fort Worth, TX, United States
^w Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Verdun, QC, Canada
^x McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
^y Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
^z Knight Alzheimer Disease Research Center, Dept of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^aa Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
^ab Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
^ac Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
^ad Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, Baltimore, MD, United States
^ae Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
^af Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, & amp; Informatics, University of Pennsylvania, Philadelphia, PA, United States
^ag Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
^ah Department of Psychosis Studies, Institute of Psychiatry, Psychology & amp; Neuroscience, King’s College London, London, United Kingdom
^ai Section for Precision Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
^aj Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States

Abstract
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.

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

Eye Movement Differences in Contact Versus Non-Contact Olympic Athletes
(2024) Journal of Motor Behavior, . 

Murray, N.P.^a , Hunfalvay, M.^b , Mesagno, C.^c , Trotter, B.^a , Monsma, E.V.^d , Greenstein, E.^e , Carrick, F.R.^f g h

^a Department of Kinesiology, Minges Coliseum, East Carolina University, 166, Greensville, NC 27858, United States
^b Research Division, RightEye LLC, Bethesda, MD, United States
^c College of Sport & Exercise Science, Institute for Health and Sport, Victoria University, Melbourne City, VIC, Australia
^d Department of Physical Education, University of South Carolina, Columbia, SC, United States
^e Department of Psychology, Washington University, St. Louis, MO, United States
^f University of Central Florida College of Medicine, Orlando, FL, United States
^g Centre for Mental Health Research in association with University of Cambridge, Cambridge, United Kingdom
^h MGH Institute for Health Professions, Boston, MA, United States

Abstract
The purpose of this study was to investigate the difference in oculomotor functioning between Olympic-level contact and non-contact sports participants. In total, 67 male and female Olympic-level contact (n = 27) and non-contact (n = 40) athletes completed oculomotor tasks, including Horizontal Saccade (HS), Circular Smooth Pursuit (CSP), Horizontal Smooth Pursuit (HSP), and Vertical Smooth Pursuit (VSP) using a remote eye tracker. No significant differences for sex or age occurred. Each variable indicated higher scores for contact compared to non-contact athletes (p &lt;.05) except for VSP Pathway differences and CSP Synchronization. A logistic regression was performed to determine the degree that HS measures, CSP synchronization, and VSP pathway predicted sport type. The model was significant, χ2(6) = 37.08, p &lt;.001, explaining 57.4% of the variance and correctly classified 88.1% of cases. The sensitivity was 87.5% and specificity was 88.9%. CSP synchronization did not increase the likelihood of participating in a contact sport. This was the first study to identify oculomotor differences between Olympic athletes of contact and non-contact sports, which adds to the growing evidence that oculomotor functioning may be a reliable, quick, real-time tool to help detect mTBI in sport. © 2024 Taylor & Francis Group, LLC.

Author Keywords
concussion;  eye tracking;  oculomotor;  sports;  traumatic brain injury

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

Negligence in biomedical research: an anti-racist approach for substance use researchers
(2024) Frontiers in Public Health, 12, art. no. 1401221, . 

Lehman, J.^a , Balangoy, D.^a , Mejia, A.P.^a , Cardenas-Iniguez, C.^b , Marek, S.^c d e f , Randolph, A.C.^a g

^a Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, United States
^b Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States
^c Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. LouisMO, United States
^d Neuroimaging Labs Research Center, Washington University School of Medicine, St. LouisMO, United States
^e Department of Psychiatry, Washington University School of Medicine, St. LouisMO, United States
^f AI Institute for Health, Washington University School of Medicine, St. LouisMO, United States
^g Department of Pediatrics, University of Minnesota, Minneapolis, MN, United States

Abstract
Racism is embedded in the fabric of society at structural, disciplinary, hegemonic, and interpersonal levels, working as a mechanism that drives health disparities. In particular, stigmatized views of substance use get entangled with racialization, serving as a tool to uphold oppressive systems. While national health institutions have made commitments to dismantle these systems in the United States, anti-racism has not been integrated into biomedical research practice. The ways in which substance use researchers use and interpret race data—without engaging in structural racism as a mechanism of health inequity—can only be described as inadequate. Drawing upon concepts from the Public Health Critical Race praxis, QuantCrit, and an anti-racism research framework, we recommend a set of guidelines to help biomedical researchers conceptualize and engage with race more responsibly in substance use research. Copyright © 2024 Lehman, Balangoy, Mejia, Cardenas-Iniguez, Marek and Randolph.

Author Keywords
antiracism;  critical race theory (CRT);  equity;  J-DEI;  racialization;  racism;  research;  substance use

Document Type: Article
Publication Stage: Final
Source: Scopus