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A structural haplotype in the 17q21.31 MAPT region is associated with increased risk for chronic traumatic encephalopathy endophenotypes

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Cell Reports Medicine 2025年第5期6卷 102084-102084页

作者： Han, Xudong Zhang, Yichi Petrosky, Jillian N. Bald, Sarah Sherva, Richard M. Labadorf, Adam Cherry, Jonathan D. Chung, Jaeyoon Farrell, Kurt Abdolmohammadi, Bobak Durape, Shruti Martin, Brett M. Palmisano, Joseph N. Farrell, John J. Alvarez, Victor E. Huber, Bertrand R. Dwyer, Brigid Daneshvar, Daniel H. Jun, Gyungah R. Lunetta, Kathryn L. Goldstein, Lee E. Katz, Douglas I. Cantu, Robert C. Shenton, Martha E. Cummings, Jeffrey L. Reiman, Eric M. Stern, Robert A. Alosco, Michael L. Tripodis, Yorghos Farrer, Lindsay A. Stein, Thor D. Crary, John F. McKee, Ann C. Mez, Jesse Bioinformatics Graduate Program Boston University Boston MA United States Section of Biomedical Genetics Department of Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Department of Neurology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston University Alzheimer's Disease Research Center Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston VA Healthcare System Boston MA United States Boston University Chronic Traumatic Encephalopathy Center Boston University Boston MA United States Department of Pathology and Laboratory Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Pathology Neuroscience and Artificial Intelligence & Human Health Neuropathology Brain Bank & Research CoRE Friedman Brain Institute Ronald M. Loeb Center for Alzheimer's Disease Icahn School of Medicine at Mount Sinai New York NY United States Biostatistics and Epidemiology Data Analytics Center Boston University School of Public Health Boston MA United States Bedford VA Healthcare System Bedford MA United States Braintree Rehabilitation Hospital Braintree MA United States Department of Physical Medicine and Rehabilitation Harvard Medical School Boston MA United States Department of Rehabilitation and Human Performance Brain Injury Research Center Icahn School of Medicine at Mount Sinai New York NY United States Department of Neurology Icahn School of Medicine at Mount Sinai New York NY United States Department of Biostatistics Boston University School of Public Health Boston MA United States Department of Ophthalmology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Biomedical Electrical & Computer Engineering Boston University College of Engineering Boston MA United States Departments of Radiology and Psychiatry Boston University Chobanian & Avedisia

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impact (RHI) exposure. Genetic variation in the 17q21.31 region, containing microtubule-associated protein tau (MAPT), has been implicated in tauopathies but has not been investigated in CTE. The region includes a megabase-long inversion (H1/H2) and copy-number variations, including α, β, and γ segments, which can be characterized as nine segregating structural haplotypes. We leveraged array SNP data and a reference panel across the 17q21.31 region to impute structural haplotypes and test their association with CTE endophenotypes in 447 European ancestry brain donors with RHI exposure. The H1β1γ1 haplotype was significantly associated with dementia and semi-quantitative tau burden in multiple cortical and medial temporal regions commonly affected in CTE. H1β1γ1 differential expression analyses in dorsolateral frontal cortex implicated cis-acting genes and inflammatory pathways. Taken together, the H1β1γ1 haplotype may help explain CTE heterogeneity among those with similar RHI exposure. © 2025 The Authors

关键词： 17q21.31 chronic traumatic encephalopathy dementia differential gene expression immune system MAPT repetitive head impacts structural haplotypes tauopathy traumatic brain injury

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Author Correction: Africa needs context-relevant evidence to shape its clean energy future

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Nature Energy 2024年 907页

作者： Yacob Mulugetta Lucas Somavilla Croxatto Meron Tesfamichael Abdulmutalib Yussuff Youba Sokona Philipp A. Trotter Samuel Fankhauser Jessica Omukuti Bjarne Steffen Edo Abraham Jean-Paul Adam Mekalia Paulos Aklilu Yohannes Hailu Linus Mofor S. Nadia Ouedraogo Lawrence Agbemabiese Churchill Agutu Florian Egli Abdulrasheed Isah Tobias S. Schmidt Olakunle Alao Wikus Kruger Peter Twesigye Bothwell Batidzirai Getachew Bekele Anteneh G. Dagnachew Ogunlade Davidson Fatima Denton E. Ogheneruona Diemuodeke Gebrekidan Gebresilassie Eshetu Mulualem Gebreslassie Mamadou Goundiam Haruna Kachalla Gujba Adam D. Hawkes Stephanie Hirmer Helen Hoka Mark Howells Daniel Kammen Francis Kemausuor Ismail Khennas Ifeoma Malo Minette Nago Destenie Nock Chukwumerije Okereke Benedict Probst Maria Schmidt Carlos Shenga Mohamed Sokona Jan Christoph Steckel Sebastian Sterl Bernard Tembo Julia Tomei Jim Watson Harald Winkler Department of Science Technology Engineering & Public Policy University College London London UK Responsible Technology Institute Department of Computer Science University of Oxford Oxford UK Groupe de Reflection et d’Initiatives Novatrices Bamako Mali Schumpeter School of Business and Economics University of Wuppertal Wuppertal Germany Smith School of Enterprise and the Environment University of Oxford Oxford UK Institute for Science Innovation and Society (INSIS) University of Oxford Oxford UK Climate Finance and Policy Group ETH Zurich Zurich Switzerland Department of Water Management Delft University of Technology Delft the Netherlands United Nations Economic Commission for Africa Addis Ababa Ethiopia Center for Energy & Environmental Policy University of Delaware Newark DE USA Energy and Technology Policy Group ETH Zurich Zurich Switzerland Kigali Collaborative Research Centre Kigali Rwanda IIPP Institute for Innovation and Public Purpose University College London London UK Institute of Science Technology and Policy ETH Zurich Zurich Switzerland Power Futures Lab Graduate School of Business University of Cape Town Cape Town South Africa African Union Development Agency (AUDA-NEPAD) Midrand Johannesburg South Africa School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa Ethiopia PBL Netherlands Environmental Assessment Agency the Hague the Netherlands Utrecht University Utrecht the Netherlands University of Sierra Leone Freetown Sierra Leone United Nations University–Institute for Natural Resources in Africa (UNU–INRA) Accra Ghana Department of Mechanical Engineering University of Port Harcourt Choba Nigeria Institute for Power Electronics and Electrical Drives RWTH Aachen University Aachen Germany Center of Energy Ethiopian Institute of Technology Mekelle University Mekelle Ethiopia Institute of Engineering University Grenoble Alpes Grenoble France GIZ — Africa–EU Energy Partnership (AEEP) Addis

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Automated Abdominal Aortic Calcification Assessment and Major Adverse Cardiovascular Events in People Undergoing Osteoporosis Screening

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Heart, Lung and Circulation 2024年 33卷 S394-S395页

作者： C. Smith M. Sim Z. Illyas S. Gilani D. Suter S. Reid B. Monchka M. Jafari Jozani G. Figtree J. Schousboe W. Leslie J. Lewis Nutrition & Health Innovation Research Institute Edith Cowan University Perth WA Australia Medical School University of Western Australia Perth WA Australia Centre for AI&ML School of Science Edith Cowan University Perth WA Australia Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada George and Fay Yee Centre for Healthcare Innovation University of Manitoba Winnipeg MB Canada Department of Statistics University of Manitoba Winnipeg MB Canada Faculty of Health and Medicine The University of Sydney Sydney NSW Australia Kolling Institute of Medical Research St Leonards NSW Australia Park Nicollet Clinic and HealthPartners Institute HealthPartners Minneapolis MN USA Division of Health Policy and Management University of Minnesota Minneapolis MN USA Departments of Medicine and Radiology University of Manitoba Winnipeg MB Canada Centre for Kidney Research Children's Hospital at Westmead School of Public Health Sydney Medical School The University of Sydney Sydney NSW Australia

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Evaluating the effectiveness of electric vehicle subsidies in Canada

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Procedia computer Science 2019年 155卷 519-526页

作者： Zachary Thorne Larry Hughes MASc Candidate Electrical & Computer Engineering Dalhousie University 6299 South St Halifax NS B3H 4R2 Canada Founding Fellow at the MacEachen Institute of Public Policy Dalhousie University 6299 South St Halifax NS B3H 4R2 Canada

The electrification of transportation has been identified as a necessary aspect of climate change mitigation in order to limit global temperatures to 1.5°C above pre-industrial levels and prevent potentially catastrophic effects on the environment. Despite this, in Canada and most other developed countries, consumers have been slow to adopt electric vehicles. In March of 2019, to encourage increased adoption of electric vehicles, the government of Canada announced a new federal EV subsidy program that will offer a rebate of up to $5000 on the purchase of zero-emission vehicles. When evaluating the costs and benefits of such a program, it is important to consider that the magnitude of emissions reductions achieved through EV subsidies relates to the emissions intensity of the electricity used to power the EV. In this paper, the cost-effectiveness of achieving emissions reductions through EV subsidy programs is evaluated with respect to each provincial electricity system in Canada. These results were then used to compare the cost-efficiency of EV subsidies to other investments in climate change mitigation initiatives, and ultimately decide whether EV subsidies are feasible to implement in any of Canada’s provinces.

关键词： electric vehicles EV subsidies sustainable energy policy climate change mitigation

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Power system dispatch with electrochemical energy storage

arXiv

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arXiv 2019年

作者： He, Guannan Kar, Soummya Mohammadi, Javad Moutis, Panayiotis Whitacre, Jay F. Department of Engineering and Public Policy Wilton E. Scott Institute for Energy Innovation Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States MIT Energy Initiative Massachusetts Institute of Technology CambridgeMA02139 United States

Electrochemical energy storage (EES) is essential for the future smart grid. The inevitable cell degradation renders the EES lifetime volatile and highly dependent on EES dispatch, and thus incurs opportunity cost. This paper rigorously derives the marginal degradation cost of EES for power system dispatch. The derived optimal marginal degradation cost is time-variant to reflect the time value of money and the functionality fade of EES and takes the form of a constant value divided by a discount factor plus a term related to EES state of health. In case studies, we demonstrate the evolution of the optimal marginal costs of degradation that corresponds to the optimal long-term dispatch outcome. We also show that the optimal marginal cost of degradation depends on the marginal cost of generation in the grid. Copyright © 2019, The Authors. All rights reserved.

关键词： Electric load dispatching

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arXiv

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arXiv 2020年

作者： Li, Jiashuo Zhou, Sili Wei, Wendong Qi, Jianchuan Li, Yumeng Chen, Bin Zhang, Ning Guan, Dabo Qian, Haoqi Wu, Xiaohui Miao, Jiawen Chen, Long Liang, Sai Feng, Kuishuang Institute of Blue and Green Development Shandong University Weihai264209 State Key Laboratory of Coal Combustion School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan430074 China School of International and Public Affairs Shanghai Jiao Tong University Shanghai200030 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Beijing Normal University Beijing100875 China Laboratory of Anthropogenic Systems Ecology College of Engineering Peking University Beijing100871 China Department of Earth System Science Tsinghua University Beijing100871 China Institute for Global Public Policy Fudan University Shanghai200433 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Key Laboratory of Geographic Information Science Ministry of Education School of Geographic Sciences East China Normal University Shanghai200241 China

China has implemented retrofitting measures in coal-fired power plants (CFPPs) to reduce air pollution through small unit shutdown (SUS), the installation of air pollution control devices (APCDs) and power generation efficiency (PGE) improvement. The reductions in highly toxic Hg emissions and their related health impacts by these measures have not been well studied. To refine mitigation options, we evaluated the health benefits of reduced Hg emissions via retrofitting measures during China's 12th Five-Year Plan by combining plant-level Hg emission inventories with the China Hg Risk Source-Tracking Model. We found that the measures reduced Hg emissions by 23.5 tons (approximately 1/5 of that from CFPPs in 2010), preventing 0.0021 points of per-foetus intelligence quotient (IQ) decrements and 114 deaths from fatal heart attacks. These benefits were dominated by CFPP shutdowns and APCD installations. Provincial health benefits were largely attributable to Hg reductions in other regions. We also demonstrated the necessity of considering human health impacts, rather than just Hg emission reductions, in selecting Hg control devices. This study also suggests that Hg control strategies should consider various factors, such as CFPP locations, population densities and trade-offs between reductions of total Hg (THg) and Hg2+. Copyright © 2020, The Authors. All rights reserved.

关键词： Fossil fuel power plants

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Examining Interconnection and Net Metering policy for Distributed Generation in the United States

SSRN

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SSRN 2019年

作者： Schelly, Chelsea Louie, Edward P. Pearce, Joshua M. Dept. of Social Sciences Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States School of Public Policy Oregon State University CorvallisOR97331-3703 United States Materials Science and Engineering Department of Electrical & Computer Engineering Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States

Following requirements of the Energy policy Act of 2005, most U.S. states require utility companies to adopt interconnection and net metering policies, allowing customers to become prosumers who both consume and produce electricity, generating electricity using distributed renewable energy technologies, connecting to the existing electric utility grid and receiving compensation for excess electricity generation. This paper reviews existing interconnection and net metering policies instituted by investor owned utilities (IOUs) across the U.S., specifically focused on policies regulating installations of small scale, residential or Tier 1 (a term used to indicate policies applicable to smaller scale rather than larger scale, although the size at which DG systems are classified as either Tier 1 or higher tiers varies by utility). publicly available data from each IOU reveal inconsistencies in interconnection and net metering policies, within states and even within individual companies. In addition, accurate information is often unavailable to consumers. Perhaps most importantly, results suggest that compensation for excess distributed generation often lacks transparent articulation in utility policy. The results of this study provide important insight into interconnection and net metering policies for distributed renewable energy generation, as states and utilities continue to modify interconnection and net metering policies in response to increased adoption of distributed renewable energy systems. © 2019, The Authors. All rights reserved.

关键词： Electric utilities

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Comparison of Gait Speed Estimation of Multiple Sensor-Based Technologies

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Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2019年第1期8卷 135 - 139页

作者： Plinio P. Morita Adson S. Rocha George Shaker Doojin Lee Jing Wei Brandon Fong Anjali Thatte Amir-Hossein Karimi Lin Lin Xu Avery Ma Alex Wong Jennifer Boger School of Public Health and Health Systems University of WaterlooCentre for Global eHealth Innovation Techna Institute University Health NetworkInstitute of Health Policy Management and Evaluation University of TorontoDepartment of Systems Design Engineering University of WaterlooResearch Institute for Aging University of WaterlooWaterloo Artificial Intelligence Institute University of Waterloo School of Public Health and Health Systems University of WaterlooGoiano Federal Institute Research Institute for Aging University of WaterlooDepartment of Electrical and Computer Engineering University of WaterlooDepartment of Mechanical and Mechatronics Engineering University of WaterlooWaterloo Artificial Intelligence Institute University of Waterloo Department of Mechanical and Mechatronics Engineering University of Waterloo Department of Systems Design Engineering University of Waterloo Department of Systems Design Engineering University of WaterlooResearch Institute for Aging University of WaterlooWaterloo Artificial Intelligence Institute University of Waterloo Department of Systems Design Engineering University of WaterlooResearch Institute for Aging University of Waterloo

In light of our aging population, there is an immediate need for non-obtrusive, continuous, and ubiquitous health monitoring technologies that will enable our population to age with a higher quality of life and independence. Research has demonstrated that gait indicators, such as walking speed, can reflect cognitive and physical functioning. However, gradual changes in such indicators usually go undetected until critical problems arise; being able to detect changes in indicators, such as gait deterioration, of older adults while in their home environments would enable clinicians to tailor more effective and personalized interventions by better understanding user behaviour in real-world settings. Real-world data is essential to enabling our healthcare system to act where patients most need help and to optimize the effect of designed eHealth solutions.

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Vaccinations or Non-Pharmaceutical Interventions: Safe Reopening of Schools in England

Research Square

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Research Square 2021年

作者： Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Aylett-Bullock, Joseph Lawrence, Bryan N. Fong, Kevin Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Vernon, Ian Williams, Julian Pagel, Christina Krauss, Frank Institute for Data Science Durham University Durham United Kingdom Institute for Computational Cosmology Durham University Durham United Kingdom Institute for Particle Physics Phenomenology Durham University Durham United Kingdom National Centre for Atmospheric Science University of Reading Reading United Kingdom Departments of Meteorology and Computer Science University of Reading Reading United Kingdom Department of Science Technology Engineering and Public Policy University College London London United Kingdom Department of Anaesthesia University College London Hospital London United Kingdom Centre for Extragalactic Astronomy Durham University Durham United Kingdom Department of Mathematical Sciences Durham University DurhamDH1 3LE United Kingdom Institute for Hazard Risk & Resilience Durham University DurhamDH1 3LE United Kingdom Clinical Operational Research Unit University College London United Kingdom

With high levels of the Delta variant of COVID-19 circulating in England during September 2021, schools are set to reopen with few school-based non-pharmaceutical interventions (NPIs). In this paper, we present simulation results obtained from the individual-based model, JUNE, for English school opening after a prior vaccination campaign using an optimistic set of assumptions about vaccine efficacy and the likelihood of prior-reinfection. We take a scenario-based approach to modelling potential interventions to assess relative changes rather than real-world forecasts. Specifically, we assess the effects of vaccinating those aged 16-17, those aged 12-17, and not vaccinating children at all relative to only vaccinating the adult population, addressing what might have happened had the UK began teenage vaccinations earlier. Vaccinating children in the 12-15 age group would have had a significant impact on the course of the epidemic, saving thousands of lives overall in these simulations. In the absence of such a vaccination campaign our simulations show there could still be a significant positive impact on the epidemic (fewer cases, fewer deaths) by continuing NPI strategies in schools. Our analysis suggests that the best results in terms of lives saved are likely derived from a combination of the now planned vaccination campaign and NPIs in schools. © 2021, CC BY.

关键词： COVID-19

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Contrastive Structured Anomaly Detection for Gaussian Graphical Models

Contrastive Structured Anomaly Detection for Gaussian Graphi...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Abhinav Maurya Mark Cheung Heinz College of Information Systems and Public Policy Carnegie Mellon University Department of Electrical and Computer Engineering Carnegie Mellon University

ISBN: (纸本)9781538660522

Gaussian graphical models (GGMs) are probabilistic tools of choice for analyzing conditional dependencies between variables in complex networked systems such as social networks, sensor networks, financial markets, etc. Finding changepoints in the structural evolution of a GGM is therefore essential to detecting anomalies in the underlying system modeled by the GGM. In order to detect structural anomalies in a GGM, we consider the problem of estimating changes in the precision matrix of the corresponding multivariate Gaussian distribution. We take a two-step approach to solving this problem:- (i) estimating a background precision matrix using system observations from the past without any anomalies, and (ii) estimating a foreground precision matrix using a sliding temporal window during anomaly monitoring. Our primary contribution is in estimating the foreground precision using a novel contrastive inverse covariance estimation procedure. In order to accurately learn only the structural changes to the GGM, we maximize a penalized log-likelihood where the penalty is the l 1 norm of difference between the foreground precision being estimated and the already learned background precision. We suitably modify the alternating direction method of multipliers (ADMM) algorithm for sparse inverse covariance estimation to perform contrastive estimation of the foreground precision matrix. Our results on simulated GGM data show significant improvement in precision and recall for detecting structural changes to the GGM, compared to a non-contrastive sliding window baseline.

关键词： Graphical models Image edge detection Covariance matrices Sparse matrices Anomaly detection Optimization Estimation

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