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Neuromuscular fatigue detection by mechanomyography in people with complete spinal cord injury

Research on Biomedical Engineering 2020年第3期36卷 203-212页

作者： Krueger, Eddy Popović-Maneski, Lana Neto, Guilherme Nunes Nogueira Mendonça Scheeren, Eduardo Fiusa, Jessika Mehret Nohama, Percy Neural Engineering and Rehabilitation Laboratory Universidade Estadual de Londrina LondrinaPR Brazil Graduate Program in Rehabilitation Sciences UEL-UNOPAR Campus Universitário s/n zipcode LondrinaPR86051-990 Brazil Institute of Technical Sciences of the Serbian Academy of Sciences and Arts KnezMihailova 35/IV zipcode Belgrade11000 Serbia Graduate Program in Health Technology Pontifícia Universidade Católica do Paraná Rua Imaculada Conceição 1155 Prado Velho zipcode CuritibaPR80215-901 Brazil Graduate Program in Electrical and Computer Engineering Universidade Tecnológica Federal do Paraná Av. Sete de Setembro 3165 zipcode CuritibaPR80230-901 Brazil

Purpose: Functional electrical stimulation (FES) is a method of activating paralyzed muscles. During FES application, fast muscle fatigue can occur (the inability of stimulated muscles to generate force). Therefore, it is beneficial to estimate the muscle fatigue for FES closed-loop control for walking to prevent unexpected muscle collapse and adapt the FES strategy in real time. Mechanomyography (MMG) is a noninvasive technique for registering myofiber vibrations, representing an ideal candidate for the provision of feedback. The hypothesis was that MMG signals could effectively detect muscle fatigue and, thus, provide feedback. Methods: We tested this hypothesis by analyzing the wavelet transform of signals from an MMG sensor positioned over the rectus femoris muscle during electrically evoked contractions in subjects with spinal cord injury (SCI). The signals were collected from a total of 24 lower limb muscles. We investigated both legs of 15 participants with spinal cord injury (male, YOA = 27.13 ± 5.05, M = 75.8 ± 10.35 kg, and H = 1.78 ± 0.07 m, American Spinal Injury Impairment Scale (AIS) A and B). All MMG signals were analyzed in 12 frequency bands from 5 to 53 Hz. Results: We found different trends in the magnitudes in different frequency bands. The magnitude decreased in 13, 16, 20, 25, and 35 Hz bands in correlation with fatigue. The greatest statistical difference was found at 20 Hz and 25 Hz. Conclusion: This result suggests that processed MMG signals indicate muscle fatigue and can, thus, be used as the feedback in FES systems. © 2020, Sociedade Brasileira de Engenharia Biomedica.

关键词： Muscle

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Is Attention All You Need for EEG to Predict Neurological Outcomes in Cardiac Arrest?

Is Attention All You Need for EEG to Predict Neurological Ou...

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IEEE EMBS International Conference on Information technology Applications in Biomedicine (ITAB)

作者： Jefferson Dionisio Muhammad Rizwan Hidetaka Suzuki Kazi Mahmudul Hassan Ingon Chanpornpakdi Lian-Yu Lin Toshihisa Tanaka Che Lin Department of Smart Medicine and Health Informatics National Taiwan University Taipei Taiwan Artificial Intelligence of Things Taiwan International Graduate Program Academia Sinica Taipei Taiwan Tokyo University of Agriculture and Technology Tokyo Japan Department of Emergency and Critical Care Japanese Red Cross Musashino Hospital Tokyo Japan Department of Internal Medicine Division of Cardiology National Taiwan University College of Medicine and Hospital Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine National Taiwan University Taipei Taiwan

ISBN: (数字)9798350351552

ISBN: (纸本)9798350351569

Sudden cardiac arrest (SCA) poses a significant health challenge, necessitating accurate predictions of neurological outcomes in comatose patients, where good outcomes are defined as the recovery of most cognitive functions. Electroencephalogram (EEG) serves as a valuable biomarker for monitoring neurological states due to its rich, time-dependent information. This study aims to predict neurological outcomes using early EEG data by employing the Transformer model, which leverages multi-headed attention to identify patterns in lengthy sequences such as hour-long EEG recordings. Unlike traditional methods that use subsampled EEG epochs, we utilize the entire EEG sequences, subdivided into time steps, allowing our model to capture detailed temporal patterns via the attention mechanism. Moreover, we trained our proposed model using each EEG recording as an individual data sample but evaluated our model through aggregated patient-wise predictions. This approach allows us to boost the data sample size. Our results demonstrate promising predictive performance, achieving an AUROC of 0.82 and AUPRC of 0.90 on the holdout test set and an AUROC of 0.73 and AUPRC of 0.93 on an external test set with patient-wise predictions. This study highlights the potential of utilizing attention mechanisms to capture important time series progressions across EEG sequences for improving SCA prognosis.

关键词： Attention mechanisms Biological system modeling Time series analysis Cardiac arrest Predictive models Brain modeling Transformers Electroencephalography Data models Recording

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The mitochondrial stress signaling tunes immunity from a view of systemic tumor microenvironment and ecosystem

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iScience 2024年第9期27卷

作者： Kuo, Cheng-Liang Lin, Ying-Chen Lo, Yu Kang Lu, Yu-Zhi Babuharisankar, Ananth Ponneri Lien, Hui-Wen Chou, Han-Yu Lee, Alan Yueh-Luen National Institute of Cancer Research National Health Research Institutes Miaoli Zhunan 35053 Taiwan Department of Life Sciences College of Health Sciences & Technology National Central University Taoyuan Zhongli 32001 Taiwan Ph.D. Program in Tissue Engineering and Regenerative Medicine College of Medicine National Chung Hsing University Taichung 40402 Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung 40402 Taiwan Department of Biotechnology College of Life Science Kaohsiung Medical University Kaohsiung 80708 Taiwan

Mitochondria play important roles in cell fate, calcium signaling, mitophagy, and the signaling through reactive oxygen species (ROS). Recently, mitochondria are considered as a signaling organelle in the cell and communicate with other organelles to constitute the mitochondrial information processing system (MIPS) that transduce input-to-output biological information. The success in immunotherapy, a concept of systemic therapy, has been proved to be dependent on paracrine interactions within the tumor microenvironment (TME) and distant organs including microbiota and immune components. We will adopt a broader view from the concept of TME to tumor micro- and macroenvironment (TM²E) or tumor-organ ecosystem (TOE). In this review, we will discuss the role of mitochondrial signaling by mitochondrial ROS, calcium flux, metabolites, mtDNA, vesicle transportation, and mitochondria-derived peptide in the TME and TOE, in particular immune regulation and effective cancer immunotherapy. © 2024 The Author(s)

关键词： Cancer Immune response Microenvironment

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Renoprotection Induced by Aerobic Training Is Dependent on Nitric Oxide Bioavailability in Obese Zucker Rats

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Oxidative Medicine and Cellular Longevity 2021年第1期2021卷 3683796页

作者： Neves, Rodrigo Vanerson Passos Corrêa, Hugo De Luca De Sousa Neto, Ivo Vieira Souza, Michel Kendy Costa, Fernando Haro, Anderson Sola Deus, Lysleine Alves Reis, Andrea Lucena Simões, Herbert Gustavo Andrade, Rosângela Vieira Assumpção, Cláudio Oliveira Stone, Whitley Prestes, Jonato Vieira, Elaine Cristina De Cássia Marquetti Durigan, Rita Cruzat, Vinicius Rosa, Thiago S. Graduate Program in Physical Education Catholic University of Brasília Brasília Brazil Laboratory of Molecular Analysis Graduate Program of Sciences and Technology of Health Universidade de Brasília Distrito Federal Brazil Department of Nephrology Federal University of São Paulo São Paulo Brazil Graduate Program in Genomic Sciences and Biotechnology Universidade Católica de Brasília Brasília Brazil Department of Physical Education Federal University of Ceará Ceará Brazil School of Kinesiology Recreation and Sport Western Kentucky University Bowling GreenKY United States Faculty of Health Torrens University Australia Brisbane Australia

Aerobic training (AT) promotes several health benefits that may attenuate the progression of obesity associated diabetes. Since AT is an important nitric oxide (NO-) inducer mediating kidney-healthy phenotype, the present study is aimed at investigating the effects of AT on metabolic parameters, morphological, redox balance, inflammatory profile, and vasoactive peptides in the kidney of obese-diabetic Zucker rats receiving L-NAME (N(omega)-nitro-L-arginine methyl ester). Forty male Zucker rats (6 wk old) were assigned into four groups (n=10, each): sedentary lean rats (CTL-Lean), sedentary obese rats (CTL-Obese), AT trained obese rats without blocking nitric oxide synthase (NOS) (Obese+AT), and obese-trained with NOS block (Obese+AT+L-NAME). AT groups ran 60 min in the maximal lactate steady state (MLSS), five days/wk/8 wk. Obese+AT rats improved glycemic homeostasis, SBP, aerobic capacity, renal mitochondria integrity, redox balance, inflammatory profile (e.g., TNF-α, CRP, IL-10, IL-4, and IL-17a), and molecules related to renal NO- metabolism (klotho/FGF23 axis, vasoactive peptides, renal histology, and reduced proteinuria). However, none of these positive outcomes were observed in CTL-Obese and Obese+AT+L-NAME (p © 2021 Rodrigo Vanerson Passos Neves et al.

关键词： Nitric oxide

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Computational models of astrocyte function at glutamatergic synapses

arXiv

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arXiv 2024年

作者： Lenk, Kerstin Denizot, Audrey Genocchi, Barbara Seppälä, Ippa Taheri, Marsa Nadkarni, Suhita Institute of Neural Engineering Graz University of Technology Graz Austria BioTechMed Graz8010 Austria Theoretical Sciences Visiting Program Okinawa Institute of Science and Technology Graduate University Onna Japan Okinawa Institute of Science and Technology Computational Neuroscience Unit Onna-Son Japan AIstroSight Inria Hospices Civils de Lyon Université Claude Bernard Lyon 1 Villeurbanne France University of Lyon LIRIS UMR5205 Villeurbanne France Faculty of Medicine and Health Technology Tampere University Tampere Finland Department of Psychology and Speech-Language Pathology University of Turku Turku Finland Department of Neurobiology University of California Los AngelesCA United States Department of Biology Indian Institute of Science Education and Research Pune India

At tripartite synapses, astrocytes are in close contact with neurons and contribute to various functions, from synaptic transmission, maintenance of ion homeostasis and glutamate uptake to metabolism. However, disentangling the precise contribution of astrocytes to those phenomena and the underlying biochemical mechanisms is remarkably challenging. This notably results from their highly ramified morphology, the nanoscopic size of the majority of astrocyte processes, and the poorly understood information encoded by their spatiotemporally diverse calcium signals. This book chapter presents selected computational models of the involvement of astrocytes in glutamatergic transmission. The goal of this chapter is to present representative models of astrocyte function in conjunction with the biological questions they can investigate. © 2024, CC BY-NC-SA.

关键词： Calcium

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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A Unified Framework for Human Centered Design of a Substance Use, Abuse, and Recovery Support System

A Unified Framework for Human Centered Design of a Substance...

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AHFE Virtual Conference on Human Factors and Ergonomics in healthcare and Medical Devices, and the International Conference on Human Factors in Aging and Special Needs, 2020

作者： Schooley, Benjamin Feldman, Sue Tipper, Bradley Health Information Technology Program College of Engineering and Computing University of South Carolina 550 Assembly Street ColumbiaSC29208 United States Graduate Programs in Health Informatics Department of Health Services Administration School of Health Professions University of Alabama - Birmingham 1716 9th Ave South SHPB #590K BirminghamAL35294 United States

ISBN: (纸本)9783030508371

This research explores the analysis, design, and testing of a software application to support opioid peer specialists working to assist substance users, abusers, those in recovery, and their families. The paper presents a framework integrating best practice approaches from Design Science Research, Community Based Participatory Research, and human centered and user experience design principles for the purpose of: 1) guiding community based, goal-directed software design, and 2) building and evaluating a substance use, abuse, and recovery software application. Focus group findings from 33 participants suggest that using the framework enables alignment between human centered system requirements;personal, family, and community-based program goal achievement;and local/state population health directives. End user feedback indicates that the software application design addresses specific human interaction needs for the complex high-stakes context of opioid use, abuse, and recovery. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Application programs

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Accelerated Discovery of Solvation Structure Engineering for Stable Aqueous Rechargeable Zinc Batteries via Physics-Guided Bayesian Active Learning (Small 23/2025)

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Small 2025年第23期21卷

作者： Minsu Kim Minji Lee Inyoung Choi Jihye Oh Sanga Paik Areum Han Sinae Lee Hyerim Hwang Jonggeol Na Kwan Woo Nam Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Chemical Engineering and Materials Science Graduate Program in System Health Science and Engineering Ewha Womans University Seoul 03760 Republic of Korea

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Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma:the PLANET study

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National Science Review 2022年第3期9卷 96-109页

作者： Weiwei Zhai Hannah Lai Neslihan Arife Kaya Jianbin Chen Hechuan Yang Bingxin Lu Jia Qi Lim Siming Ma Sin Chi Chew Khi Pin Chua Jacob Josiah Santiago Alvarez Pauline Jieqi Chen Mei Mei Chang Lingyan Wu Brian K.P.Goh Alexander Yaw-Fui Chung Chung Yip Chan Peng Chung Cheow Ser Yee Lee Juinn Huar Kam Alfred Wei-Chieh Kow Iyer Shridhar Ganpathi Rawisak Chanwat Jidapa Thammasiri Boon Koon Yoong Diana Bee-Lan Ong Vanessa H.de Villa Rouchelle D.Dela Cruz Tracy Jiezhen Loh Wei Keat Wan Zeng Zeng Anders Jacobsen Skanderup Yin Huei Pang Krishnakumar Madhavan Tony Kiat-Hon Lim Glenn Bonney Wei Qiang Leow Valerie Chew Yock Young Dan Wai Leong Tam Han Chong Toh Roger Sik-Yin Foo Pierce Kah-Hoe Chow Genome Institute of Singapore Agency for Science Technology and Research Key Laboratory of Zoological Systematics and Evolution Institute of Zoology Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences School of Biological Sciences Nanyang Technological University Division of Biosciences Faculty of Life Sciences Division of Surgery and Surgical Oncology National Cancer Centre Department of Hepato-Pancreato-Biliary and Transplant Surgery Singapore General Hospital Division of Hepatobiliary and Pancreatic Surgery Department of Surgery University Surgical Cluster National University Health System Hepato-Pancreato-Biliary Surgery Unit Department of Surgery National Cancer Institute Division of Pathology National Cancer Institute Department of Surgery Faculty of Medicine University of Malaya Department of Surgery and Center for Liver Disease Management and Transplantation The Medical City Department of Laboratories The Medical City Department of Pathology Singapore General Hospital Institute for Infocomm Research ASTAR Department of Pathology National University Health System Translational Immunology Institute (TII) Sing Health Duke-NUS Academic Medical Centre Division of Gastroenterology and Hepatology University Medicine Cluster National University Hospital Department of Biochemistry Yong Loo Lin School of Medicine National University of Singapore Cancer Science Institute of Singapore National University of Singapore Division of Medical Oncology National Cancer Center Singapore Cardiovascular Research Institute National University of Singapore National University Healthcare System Singhealth-Duke-NUS Academic Surgery Program Duke-NUS Graduate Medical School Institute of Molecular and Cell Biology Agency for Science Technology and Research

Intra-tumor heterogeneity(ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic(transcriptomic and immune)heterogeneity. Using one of the largest prospective surgical cohorts for hepatocellular carcinoma(HCC)with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients(331 samples). We found that while genomic ITH was rather constant across stages, phenotypic ITH had a very different trajectory and quickly diversified in stage Ⅱ patients. Most strikingly, 30% of patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types.

关键词： hepatocellular carcinoma intra-tumor heterogeneity phenotypic evolution tumor evolution

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A Novel Enhancer-AAV Approach Selectively Targeting Dentate Granule Cells

SSRN

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SSRN 2023年

作者： Banks, Emmie Gutekunst, Claire-Anne Vargish, Geoffrey A. Eaton, Anna Pelkey, Kenneth A. McBain, Chris J. Zheng, James Q. Oláh, Viktor Janos Rowan, Matthew J.M. Department of Cell Biology Emory University School of Medicine AtlantaGA30322 United States GDBBS Graduate Program Laney Graduate School Emory University United States Department of Neurosurgery Emory University School of Medicine AtlantaGA30322 United States Section on Cellular and Synaptic Physiology NICHD - Eunice Kennedy Shriver National Institute of Child Health United States Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA30322 United States BethesdaMD United States Center for Neurodegenerative Disease Emory University School of Medicine United States

The mammalian brain contains the most diverse array of cell types of any organ, including dozens of neuronal subtypes with distinct anatomical and functional characteristics. The brain leverages these neuron-type-specializations to perform diverse circuit operations and thus execute different behaviors properly. Through the use of Cre lines, access to specific neuron types has steadily improved over past decades. Despite their extraordinary utility, development and cross-breeding of Cre lines is time-consuming and expensive, presenting a significant barrier to entry for many investigators. Furthermore, cell-based therapeutics developed in Cre mice are not clinically translatable. Recently, several AAV vectors utilizing neuron-type-specific regulatory transcriptional sequences (enhancer-AAVs) were developed which overcome these limitations. Using a publicly available RNAseq dataset, we evaluated the potential of several candidate enhancers for neuron-type-specific targeting in the hippocampus. Here we identified a promising enhancer-AAV for targeting dentate granule cells and validated its selectivity in wild-type adult mice. © 2023, The Authors. All rights reserved.

关键词： Neurons

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