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Cognitive disorder and dementia in type 2 diabetes mellitus

World Journal of Diabetes 2022年第4期13卷 319-337页

作者： Genaro G Ortiz Miguel Huerta Héctor A González-Usigli Erandis D Torres-Sánchez Daniela LC Delgado-Lara Fermín P Pacheco-Moisés Mario A Mireles-Ramírez Blanca MG Torres-Mendoza Roxana I Moreno-Cih Irma E Velázquez-Brizuela Department of Philosophical and Methodological Disciplines University Health Sciences CenterUniversity of GuadalajaraGuadalajara 44340JaliscoMexico Department of Neurology Movement Disorders ClinicSub-Specialty Medical UnitNational Western Medical CenterMexican Social Security Institute(IMSS)Guadalajara 44340JaliscoMexico University Biomedical Research Center University of ColimaColima 28040Mexico Department of Medical and Life Sciences University Center of‘La Ciénega’University of GuadalajaraOcotlán 47810JaliscoMexico Department of Chemistry University Center of Exact Sciences and EngineeringUniversity of GuadalajaraGuadalajara 44340JaliscoMexico Division of Neurosciences Western Biomedical Research CenterMexican Social Security Institute(IMSS)Guadalajara 44340JaliscoMexico Gerontology Postgraduate Program Public Health DepartmentUniversity Health Sciences CenterUniversity of GuadalajaraGuadalajara 44340JaliscoMexico

Insulin,a key pleiotropic hormone,regulates metabolism through several signaling pathways in target tissues including skeletal muscle,liver,and *** the brain,insulin modulates learning and memory,and impaired insulin signaling is associated with metabolic dysregulation and neurodegenerative *** the receptor level,in aging and Alzheimer’s disease(AD)models,the amount of insulin receptors and their functions are *** and animal model studies suggest that memory improvements are due to changes in insulin ***,diabetes mellitus(DM)and insulin resistance are associated with age-related cognitive decline,increased levels ofβ-amyloid peptide,phosphorylation of tau protein;oxidative stress,pro-inflammatory cytokine production and dyslipidemia. Recent evidence shows that deleting brain insulin receptors leads to mildobesity and insulin resistance without influencing brain size and apoptosis ***, deleting insulin-like growth factor 1 receptor (IGF-1R) affects brain size anddevelopment, and contributes to behavior changes. Insulin is synthesized locally in the brain andis released from the neurons. Here, we reviewed proposed pathophysiological hypotheses toexplain increased risk of dementia in the presence of DM. Regardless of the exact sequence ofevents leading to neurodegeneration, there is strong evidence that mitochondrial dysfunctionplays a key role in AD and DM. A triple transgenic mouse model of AD showed mitochondrialdysfunction, oxidative stress, and loss of synaptic integrity. These alterations are comparable tothose induced in wild-type mice treated with sucrose, which is consistent with the proposal thatmitochondrial alterations are associated with DM and contribute to AD development. Alterationsin insulin/IGF-1 signaling in DM could lead to mitochondrial dysfunction and low antioxidantcapacity of the cell. Thus, insulin/IGF-1 signaling is important for increased neural processing andsystemic metabolism, a

关键词： Alzheimer´s disease Diabetes mellitus Insulin Vascular dementia Cognitive decline

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Novel Circuit Design for a 3D Position Sensitive Scintillation TOF-PET Detector that Achieves ~100 ps CTR

Novel Circuit Design for a 3D Position Sensitive Scintillati...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Shirin Pourashraf Zhixiang Zhao Derek Innes Andrea Gonzalez-Montoro Joshua W. Cates Craig S. Levin Department of Radiology Stanford University Stanford CA USA Shanghai Jiao Tong University School of Biomedical EngineeringShanghaiPeople's Republic of China Applied Nuclear Physics Program Lawrence Berkeley National Laboratory Berkeley CA USA Departments of Radiology Bioengineering Physics and Electrical Engineering Molecular Imaging Program Stanford University Stanford CA USA

We have built a scalable mixed-signal readout circuit for a 3D position sensitive PET detector that achieves ~100 ps FWHM CTR. For this work we used individual 3×3×3 mm 3 and 3×3×10 mm 3 LGSO crystals, as well as 2×4 arrays of 3×3×10 mm 3 crystals side-coupled to arrays of 3.16×3.16 mm 2 SiPMs. The preliminary results verify that the CPLD is able to resolve 3D interaction positions along the array with < 3 mm positioning resolution along the length of each 10 mm long crystal element. We also present the readout strategy to compensate the CPLD digital noise that otherwise reduces the sensitivity and CTR performance. With this novel strategy we achieved nearly %100 sensitivity recovery as well as ~11 ps improved CTR.

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Journal of Neurophysiology 2025年第6期133卷 1761-1794页

作者： Jacob Salminen Chang Liu Erika M. Pliner Madison Tenerowicz Arkaprava Roy Natalie Richer Jungyun Hwang Chris J. Hass David J. Clark Rachael D. Seidler Todd M. Manini Yenisel Cruz-Almeida Daniel P. Ferris Department of Biomedical Engineering University of Florida Gainesville Florida United States Department of Kinesiology and Nutrition University of Illinois Chicago Chicago Illinois United States Department of Mechanical Engineering University of Utah Salt Lake City Utah United States Department of Biostatistics University of Florida Gainesville Florida United States Department of Kinesiology and Applied Health University of Winnipeg Winnipeg Manitoba Canada Department of Neurology University of Florida Gainesville Florida United States Department of Applied Physiology and Kinesiology University of Florida Gainesville Florida United States Brain Rehabilitation Research Center Malcom Randall VA Medical Center Gainesville Florida United States Norman Fixel Institute for Neurological Diseases University of Florida Gainesville Florida United States McKnight Brain Institute University of Florida Gainesville Florida United States Department of Health Outcomes and Biomedical Informatics University of Florida Gainesville Florida United States Department of Community Dentistry and Behavioral Science University of Florida Gainesville Florida United States Pain Research and Intervention Center of Excellence University of Florida Gainesville Florida United States Department of Neuroscience University of Florida Gainesville Florida United States

Preferred and maximum walking speeds decline as we age, and the decline has been associated with worsening health. Slowing of gait in older individuals is correlated with biomechanical and neural factors, but historically it has been difficult to measure whole brain activity during walking. Recent advances in mobile brain imaging with high-density electroencephalography (EEG) allow for separation and localization of electrical brain activity during walking. We studied younger (N = 31) and older (N = 59) adults walking on a treadmill at different speeds (0.25–1.0 m/s) while we recorded electrocortical dynamics with EEG. We hypothesized that faster walking speeds would result in greater sensorimotor and posterior parietal theta-band (4–7 Hz) spectral power and lower beta-band (13–30 Hz) spectral power compared to slower walking speeds for older adults, consistent with previous studies on younger adults. Additionally, we used a standardized test of physical function to group older adults into high-functioning [Short Physical Performance Battery (SPPB) ≥ 10] and low-functioning (SPPB < 10) groups for comparison. In agreement with our hypotheses, sensorimotor and posterior parietal theta power increased and beta power decreased at faster walking speeds. We also found that left posterior parietal, mid cingulate, and cuneus exhibited differences in theta power at faster speeds between younger and older adults. The results suggest that older and younger adults activate cortical areas throughout the brain while walking at different speeds and older adults, particularly those with lower mobility, recruit greater cognitive resources in parietal cortex compared to younger adults. These results could inform stimulation protocols targeting parietal cortex. NEW & NOTEWORTHY Older and younger adults show widespread EEG beta power decreases at faster walking speeds compared to slower walking speeds. Older adults differentially alter EEG theta power while walking compared to younger

关键词： aging clinical electroencephalography gait mobile brain imaging

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Development of a Self-Powered Microneedle Based Wearable Electrochemical Sensor for Glucose Monitoring

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ECS Meeting Abstracts 2023年第34期MA2023-01卷 1891-1891页

作者： Anindita Ganguly Jun-Hsuan Chung Kai Po Fan Kuei-Lin Liu Manish Kumar Sharma Zong-Hong Lin Institute of Biomedical Engineering National Tsing Hua University Dept. of Power Mechanical Engineering National Tsing Hua University Materials Science and Engineering National Tsing-Hua University Department of Biomedical Engineering National Taiwan University

Diabetes is increasingly being recognized as a worldwide public health concern owing to the affected rate of the patients in the past years. One of the major barriers to the disease control is the lack of sensitive and reliable point-of-care device that can provide quantitative diagnosis and monitoring. The wearable sensing technology has the potential of revolutionizing the precision medicine and personalized healthcare system. Within the emerging class of wearables, the microneedle-based sensors play a key role in combining the advantages of monitoring the analytes in interstitial fluid (ISF) and minimally invasive skin pricking. However, such devices require appropriate power sources to realize their full capacity, and the increasing power costs, global warming, and environmental pollution are certain aspects that needs to be pondered upon. Researches are dedicated on power generators with focus on wearable energy harvesters to address the issue of power supply. Thermoelectric generators (TEGs) have the ability to generate power by transforming thermal energy to electrical power output. Herein, we have developed a microneedle based enzymatic, electrochemical glucose sensing system powered by TEG utilizing the body heat. 1 mm stainless steel microneedles were sputtered with gold and platinum, and further coated with graphene paste, glucose oxidase, poly-hydroxyethyl methacrylate, and nafion. The fabricated device exhibited a good sensitivity, and a wide linear range. According to the World Health Organization (WHO), the normal glucose level in human body are between 4.0 mM to 5.6 mM, and our device has shown a concentration dependent output current signal from 4.0 mM to 24.0 mM. The device has also exhibited excellent detection results in real-sample (artificial ISF) in vitro study as well as in vivo analysis performed in 12 – 15 weeks SD rats. The device is completely self-powered where the TEG derives power from the temperature gradient betwe

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An in-vitro biomechanical assessment of humeral head migration following irreparable rotator cuff tear and subacromial balloon reconstruction

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Shoulder and Elbow 2020年第4期12卷 265-271页

作者： Reeves, Jacob M Singh, Supriya Langohr, G Daniel G Athwal, George S Johnson, James A Department of Mechanical Engineering The University of Western Ontario London Canada The Roth|McFarlane Hand and Upper Limb Centre St. Joseph’s Hospital London Canada Department of Surgery The University of Western Ontario London Canada Department of Biomedical Engineering The University of Western Ontario London Canada

Background: A resorbable subacromial balloon has been developed to address humeral head migration following posterosuperior rotator cuff tears. The purpose of this experimental assessment was to quantify the effect of balloon augmentation on humeral head position. Methods: Eight cadaveric shoulders were subjected to 0°, 30°, 60° and 90° of abduction via a shoulder simulator. The deltoid was activated at 40N, then 80N. The subscapularis and infraspinatus with teres minor were then applied independently and together to create four muscle activation states for each deltoid load. The shoulder was tested intact, torn, then with the balloon. The centre of the humeral head was tracked using active optical markers. Results: When the rotator cuff was torn, the humeral head translated superior by 1.4 ± 1 mm overall (P = 0.009). Following balloon augment, the humeral head translated inferiorly by 2 ± 2 mm relative to the intact state (P = 0.042), and significantly more anterior than the intact (3 ± 2 mm;P = 0.005) state. Rotator cuff variation was only significantly different when the balloon was used, with the subscapularis translating the humeral head posteriorly (P = 0.006). Discussion: The subacromial balloon inferiorized the humeral head compared to the torn state. Unexpected anterior humeral head translation was attributed to the posterosuperior balloon placement relative to the humeral head. © 2019 The British Elbow & Shoulder Society.

关键词： cuff tear arthropathy InSpace balloon proximal migration reverse shoulder arthropasty rotator cuff tear shoulder subacromial balloon

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AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms

arXiv

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arXiv 2023年

作者： Zhao, Chen Xu, Zhihui Jiang, Jingfeng Esposito, Michele Pienta, Drew Hung, Guang-Uei Zhou, Weihua Department of Applied Computing Michigan Technological University HoughtonMI United States Department of Cardiology Hospital of Nanjing Medical University Nanjing China Department of Biomedical Engineering Michigan Technological University HoughtonMI United States Department of Cardiology Medical University of South Carolina CharlestonSC United States Mechanical Engineering-Engineering Mechanics Michigan Technological University HoughtonMI United States Department of Nuclear Medicine Chang Bing Show Chwan Memorial Hospital Changhua Taiwan Center for Biocomputing and Digital Health Institute of Computing and Cyber-systems Health Research Institute Michigan Technological University HoughtonMI United States

Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in the computer-aided diagnosis of coronary artery disease (CAD). However, separating and identifying individual coronary arterial segments is challenging because morphological similarities of different branches on the coronary arterial tree and human-to-human variabilities exist. Inspired by the training procedure of interventional cardiologists for interpreting the structure of coronary arteries, we propose an association graph-based graph matching network (AGMN) for coronary arterial semantic labeling. We first extract the vascular tree from invasive coronary angiography (ICA) and convert it into multiple individual graphs. Then, an association graph is constructed from two individual graphs where each vertex represents the relationship between two arterial segments. Thus, we convert the arterial segment labeling task into a vertex classification task;ultimately, the semantic artery labeling becomes equivalent to identifying the artery-to-artery correspondence on graphs. More specifically, using the association graph, the AGMN extracts the vertex features by the embedding module, aggregates the features from adjacent vertices and edges by graph convolution network, and decodes the features to generate the semantic mappings between arteries. By learning the mapping of arterial branches between two individual graphs, the unlabeled arterial segments are classified by the labeled segments to achieve semantic labeling. A dataset containing 263 ICAs was employed to train and validate the proposed model, and a five-fold cross-validation scheme was performed. Our AGMN model achieved an average accuracy of 0.8264, an average precision of 0.8276, an average recall of 0.8264, and an average F1-score of 0.8262, which significantly outperformed existing coronary artery semantic labeling methods. In concl

关键词： Semantics

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Analysis of lockdown perception in the United States during the COVID-19 pandemic

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The European Physical Journal Special Topics 2021年第9期231卷 1625-1633页

作者： Surano, Francesco Vincenzo Porfiri, Maurizio Rizzo, Alessandro Dipartimento di Elettronica e Telecomunicazioni Politecnico di Torino Turin Italy Department of Mechanical and Aerospace Engineering Tandon School of Engineering New York University Brooklyn USA Center for Urban Science and Progress Tandon School of Engineering New York University Brooklyn USA Department of Biomedical Engineering Tandon School of Engineering New York University Brooklyn USA Office of Innovation Tandon School of Engineering New York University Brooklyn USA

Containment measures have been applied throughout the world to halt the COVID-19 pandemic. In the United States, several forms of lockdown have been adopted in different parts of the country, leading to heterogeneous epidemiological, social, and economic effects. Here, we present a spatio-temporal analysis of a Twitter dataset comprising 1.3 million geo-localized Tweets about lockdown, from January to May 2020. Through sentiment analysis, we classified Tweets as expressing positive or negative emotions about lockdown, demonstrating a change in perception during the course of the pandemic modulated by socio-economic factors. A transfer entropy analysis of the time series of Tweets unveiled that the emotions in different parts of the country did not evolve independently. Rather, they were mediated by spatial interactions, which were also related to socio-ecomomic factors and, arguably, to political orientations. This study constitutes a first, necessary step toward isolating the mechanisms underlying the acceptance of public health interventions from highly resolved online datasets.

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Dual SORT LNPs for multi-organ base editing

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Nature biotechnology 2025年 2025 Jun 2页

作者： Minjeong Kim Eunice S Song Joseph C Chen Sumanta Chatterjee Yehui Sun Sang M Lee Shiying Wu Priyanka Patel Zeru Tian Ariel Kantor Brandon A Wustman David J Lockhart Daniel J Siegwart Department of Biomedical Engineering Department of Biochemistry Simmons Comprehensive Cancer Center Program in Genetic Drug Engineering The University of Texas Southwestern Medical Center Dallas TX USA. ReCode Therapeutics Menlo Park CA USA. Department of Biomedical Engineering Department of Biochemistry Simmons Comprehensive Cancer Center Program in Genetic Drug Engineering The University of Texas Southwestern Medical Center Dallas TX USA. daniel.siegwart@utsouthwestern.edu.

Alpha-1 antitrypsin (A1AT) deficiency (AATD) is caused by a mutation in the SERPINA1 gene (PiZ allele), where misfolded A1AT liver accumulation leads to liver damage, and A1AT deficiency in the lungs results in emphysema due to unregulated neutrophil elastase activity. Base editing offers a potential cure for A1AT; however, effective treatment is hindered by the absence of dual-target delivery systems that can target key tissues. We developed Dual Selective ORgan-Targeting lipid nanoparticles (SORT LNPs) to deliver base editors to the liver and lungs. Dual SORT LNPs correct the PiZ mutation, achieving 40% correction editing in liver cells and 10% in lung AT2 cells. The liver maintains stable editing for 32 weeks, reducing Z-A1AT levels by over 80% and restoring a normal liver phenotype. In parallel, 89% neutrophil elastase inhibition is achieved in lung bronchoalveolar lavage fluid. Taken together, Dual SORT LNP therapy offers a promising approach for long-lasting genome correction for multi-organ diseases such as AATD.

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Scalable Crystal Structure Relaxation Using an Iteration-Free Deep Generative Model with Uncertainty Quantification

arXiv

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arXiv 2024年

作者： Yang, Ziduo Zhao, Yi-Ming Wang, Xian Liu, Xiaoqing Zhang, Xiuying Li, Yifan Lv, Qiujie Chen, Calvin Yu-Chian Shen, Lei Department of Mechanical Engineering National University of Singapore Singapore117575 Singapore Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen518107 China Department of Physics National University of Singapore Singapore117551 Singapore -Preferred Program School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China State Key Laboratory of Chemical Oncogenomics School of Chemical Biology and Biotechnology Peking University Shenzhen Graduate School Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong L-Med Biotechnology Co. Ltd. Guangdong Meizhou514699 China Research Institute Chongqing401123 China

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and complex twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax's reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science. Code for DeepRelax is available at https://***/Shen-Group/DeepRelax. Copyright © 2024, The Authors. All rights reserved.

关键词： Point defects

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Inferring material parameters from imprecise experiments on soft materials by virtual fields method

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Annals of Solid and Structural Mechanics 2020年第1-2期12卷 59-72页

作者： Kazerooni, N. Afsar Wang, Z. Srinivasa, A.R. Criscione, J.C. Department of Mechanical Engineering Texas A&M University College StationTX77843 United States Health Sciences Ontario Tech University 2000 Simcoe St N OshawaONL1G 0C5 Canada Department of Biomedical Engineering Texas A&M University College StationTX77843 United States

Inferring material parameters of soft materials, especially soft tissues from experiments, has always been a challenge because of the inaccuracy of specimen geometry, difficulty in proper gripping and difficulty in obtaining reliable displacement data. If one is able to obtain full field data with Digital Image Correlation or other similar techniques, we show that in spite of poor quality experimental data, it is still possible to get the material parameters using Virtual Fields Method with carefully chosen virtual fields. We demonstrate the approach by two cases. The first is Ecoflex (silicone rubber) under biaxial deformations at controlled loading rates, and the second is rat skin samples with imperfect shape under biaxial deformations at controlled loading rates. In both cases, rather than trying to obtain homogeneous deformation conditions, we use a technique based on the Virtual Fields Method to extract the material properties from the deformation of the specimen collected by Digital Image Correlation (DIC) and the force load measured by the load sensor. In order to apply loads in two principal directions simultaneously, a custom biaxial set-up was built and mounted into a uniaxial Instron tensile set-up. We show here that in spite of significant inhomogeneity in the deformation, errors, and missing data in the measured displacement field, we are still able to recover the material properties of the soft solid by suitable choices of virtual fields. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Tensile testing

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