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Regulation of sleep by astrocytes in the hypothalamic ventrolateral preoptic nucleus

Neural Regeneration Research 2025年第4期20卷 1098-1100页

作者： Jae-Hong Kim Ruqayya Afridi Il-Sung Jang Maan Gee Lee Kyoungho Suk Brain Korea 21 four KNU Convergence Educational Program of Biomedical Sciences for Creative Future Talents School of MedicineKyungpook National UniversityDaeguRepublic of Korea Department of Pharmacology School of MedicineKyungpook National UniversityDaeguRepublic of Korea Department of Pharmacology School of DentistryKyungpook National UniversityDaeguRepublic of Korea Brain Science&Engineering Institute Kyungpook National UniversityDaeguRepublic of Korea

Astrocytes are functionally dynamic cells that support neurons in multiple ways throughout an organism’s *** astrocytic regulation of neuronal activity has been increasingly recognized in recent *** are now recognized as playing a more complex role than mere bystanders in the central nervous ***,their role in regulating the sleep neurocircuitry is not well *** this perspective,we highlight the role of astrocytes in sleep modulation,with a particular focus on regulatory mechanisms related to the ventrolateral preoptic nucleus(VLPO)of the *** briefly discuss recent literature reporting the role of VLPO astrocytes in regulating sleep-associated behaviors.

关键词： sleep ventrolateral astrocytes

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Simplified Model Characterization and Control of an Unmanned Surface Vehicle

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Journal of Marine Science and engineering 2025年第4期13卷 813-813页

作者： Lovo-Ayala, Aldo Soto-Diaz, Roosvel Gutierrez-Martinez, Carlos Andres Jimenez-Vargas, Jose Fernando Jiménez-Cabas, Javier Escorcía-Gutierrez, Jose Cartagena de Indias130001 Colombia Biomedical Engineering Program Universidad Simón Bolívar Barranquilla080002 Colombia Department of Electrical and Electronic Engineering Universidad de Los Andes Bogotá111711 Colombia Barranquilla080002 Colombia

This study presents the modeling and control of the unmanned surface vehicle (USV) SABALO. Two models were built, one based on a transfer function matrix and another based on state variables, and from these models, two control strategies were developed. The first strategy is based on independent Proportional-Integral/Proportional-Derivative (PI/PD) controllers complemented by a decoupling system, and the second strategy is based on state variable feedback. The two control strategies were evaluated and contrasted. Results demonstrated that the decoupler effectively eliminated variable interaction, enhancing stability in straight trajectories and directional changes. Meanwhile, state feedback control demonstrated markedly faster response times and superior precision, accompanied by higher energy consumption. The study concludes that both strategies are effective, but their suitability depends on the mission. The decoupler could be ideal for energy-efficient, long-duration operations, while state feedback could be appropriate for dynamic environments requiring rapid maneuvers. © 2025 by the authors.

关键词： State estimation

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On the origin of memory neurons in the human hippocampus

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Trends in Cognitive Sciences 2025年第5期29卷 421-433页

作者： Kolibius, Luca D. Josselyn, Sheena A. Hanslmayr, Simon Department of Biomedical Engineering Columbia University New York CityNY United States Program in Neurosciences and Mental Health The Hospital for Sick Children TorontoON Canada Department of Physiology University of Toronto TorontoON Canada Department of Psychology University of Toronto TorontoON Canada Institute of Medical Sciences University of Toronto TorontoON Canada School of Psychology and Neuroscience and Centre for Neurotechnology University of Glasgow Glasgow United Kingdom Centre for Neurotechnology University of Glasgow Glasgow United Kingdom

The hippocampus is essential for episodic memory, yet its coding mechanism remains debated. In humans, two main theories have been proposed: one suggests that concept neurons represent specific elements of an episode, while another posits a conjunctive code, where index neurons code the entire episode. Here, we integrate new findings of index neurons in humans and other animals with the concept-specific memory framework, proposing that concept neurons evolve from index neurons through overlapping memories. This process is supported by engram literature, which posits that neurons are allocated to a memory trace based on excitability and that reactivation induces excitability. By integrating these insights, we connect two historically disparate fields of neuroscience: engram research and human single neuron episodic memory research. © 2025 The Authors

关键词： Neurons

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Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice

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Journal of Neurophysiology 2025年第2期133卷 502-512页

作者： Sharma, Ohm Mykins, Michael Bergee, Rebecca E. Price, Joshua M. O’Neil, Michael A. Mickels, Nicole Von Hagen, Megan O’Connor, James Baghdoyan, Helen A. Lydic, Ralph Neuroscience Program in Psychology The University of Tennessee Knoxville TN United States Department of Biochemistry & Cellular and Molecular Biology The University of Tennessee Knoxville TN United States Office of Innovative Technologies The University of Tennessee Knoxville TN United States Department of Microbiology The University of Tennessee Knoxville TN United States Department of Biomedical Engineering The University of Tennessee Knoxville TN United States

Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, anxiety is a latent construct that cannot be directly measured. The present study combined machine learning techniques and artificial intelligence with confirmatory factor analysis to evaluate the hypothesis that buprenorphine alters motor and anxiety-like behavior in C57BL/6J (B6) mice (n = 30) as a function of dose, sex, and body mass. After administration of saline (control) or buprenorphine, mice were placed on an elevated zero maze (EZM) for 5 min. Digital video of mouse behavior was uploaded to the cloud, and mouse position on the maze was tracked and analyzed with supervised machine learning and artificial intelligence. ANOVA and post hoc test showed that buprenorphine significantly altered five motor behaviors. Confirmatory factor analysis revealed that the latent construct of anxiety-like behavior accounted for a statistically significant amount of variance in all five motor behaviors. Copyright © 2025 the American Physiological Society.

关键词： animal emotions artificial intelligence convolutional neural network deep learning opioids

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Current advances of biodegradable and biocompatible nanofiber-based materials for tissue engineering and drug delivery

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MRS Communications 2025年 1-17页

作者： Li, Zhiming Bhaskar, Nitu Erel-Akbaba, Gulsah Zhu, Yuhui Ge, Gang Park, Jinyoung Angadi, Kishan Duhoon, Achal Nguyen, Thanh Duc Department of Biomedical Engineering University of Connecticut Storrs USA Polymer Program Institute of Materials Science University of Connecticut Storrs USA Department of Pharmaceutical Biotechnology Faculty of Pharmacy Izmir Katip Celebi University Izmir Turkey Department of Mechanical Engineering University of Connecticut Storrs USA

Nanoscale fibrous materials of natural and synthetic polymers with high porosity, flexibility, biodegradability, biocompatibility, and functionality have garnered a lot of scientific attention and present exciting opportunities for regenerative medicine and drug delivery. The potential of developing scaffolds and drug delivery systems that can overcome current barriers in the fields of medicine and pharmacy is greatly expanded by the transformation and incorporation of nanofibers into free-standing nanomembranes, 3D scaffolds, actuators, transducers or sensors, which permits localized stimulation of target tissues, promotes proliferation, and enables controlled drug release over time. This review emphasizes innovative materials, fabrication techniques, and biomedical uses of synthetic and natural nanofiber-based biomaterials. Different from the previous reviews in the field, this work at best includes literature within the last 8 years to cover new exciting functional nanofibers (such as biodegradable electroactive nanofibers) and unique medical applications of these nanofiber materials. We highlight the use of a range of recent fabrication techniques (electrospinning, phase separation, and molecular self-assembly) to enhance the physicochemical and mechanical properties as well as (bio)compatibility of nanofibers for advanced drug delivery systems and tissue engineering applications. At the end, this article provides a future perspective on the advancement of biodegradable and biocompatible nanofibers for the fields of tissue engineering and drug delivery.

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Increased deformations are dispensable for encapsulated cell mechanoresponse in engineered bone analogs mimicking aging bone marrow

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Mechanobiology in Medicine 2025年第1期3卷 100097页

作者： Regner, Alexander M. DeLeon, Maximilien Gibbons, Kalin D. Howard, Sean Nesbitt, Derek Q. Darghiasi, Seyedeh F. Zavala, Anamaria G. Lujan, Trevor J. Fitzpatrick, Clare K. Farach-Carson, Mary C. Wu, Danielle Uzer, Gunes Mechanical and Biomedical Engineering Department Boise State University United States Department of Diagnostic and Biomedical Sciences UTHealth Houston School of Dentistry United States Department of Bioengineering Rice University United States Department of Biosciences Rice University United States Biomedical Engineering Program Boise State University United States

Aged individuals and astronauts experience bone loss despite rigorous physical activity. Bone mechanoresponse is in-part regulated by mesenchymal stem cells (MSCs) that respond to mechanical stimuli. Direct delivery of low intensity vibration (LIV) recovers MSC proliferation in senescence and simulated microgravity models, indicating that age-related reductions in mechanical signal delivery within bone marrow may contribute to declining bone mechanoresponse. To answer this question, we developed a 3D bone marrow analog that controls trabecular geometry, marrow mechanics and external stimuli. Validated finite element (FE) models were developed to quantify strain environment within hydrogels during LIV. Bone marrow analogs with gyroid-based trabeculae of scaffold volume fractions (SV/TV) corresponding to adult (25 %) and aged (13 %) mice were printed using polylactic acid (PLA). MSCs encapsulated in migration-permissive hydrogels within printed trabeculae showed robust cell populations on both PLA surface and hydrogel within a week. Following 14 days of LIV treatment (1 g, 100 Hz, 1 h/day), cell proliferation, type-I collagen (Collagen-I) and filamentous actin (F-actin) were quantified for the cells in the hydrogel fraction. While LIV increased all measured outcomes, FE models predicted higher von Mises strains for the 13 % SV/TV groups (0.2 %) when compared to the 25 % SV/TV group (0.1 %). While LIV increased collagen-I volume 34 % more in 13 % SV/TV groups when compared to 25 % SV/TV groups, collagen-I and F-actin measures remained lower in the 13 % SV/TV groups when compared to 25 % SV/TV counterparts, indicating that both LIV-induced strains and scaffold volume fraction (i.e. available scaffold surface) affect cell behavior in the hydrogel phase. Overall, bone marrow analogs offer a robust and repeatable platform to study bone mechanobiology. © 2024 The Author(s)

关键词： 3D printing Low-intensity vibration Mechanical modeling Mechanical signals Mesenchymal stem cells Tissue modeling

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Reliability analysis of hospital infusion pumps: a case study

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biomedical engineering Online 2025年第1期24卷 1-21页

作者： Silva, Mayla dos S. Nunes, Maria Alzira de A. Rosa, Suélia de Siqueira R. F. Piratelli-Filho, Antônio Postgraduate Program in Integrity of Engineering Materials University of Brasilia St. Leste Projeção A - Gama Leste Distrito Federal Brasilia72.444-240 Brazil Mechanical Engineering Department University of Brasilia Campus Universitário Darcy Ribeiro Asa Norte Distrito Federal Brasilia70.910-900 Brazil Postgraduate Program in Biomedical Engineering University of Brasilia St. Leste Projeção A - Gama Leste Distrito Federal Brasilia72.444-240 Brazil Meinig School of Biomedical Engineering Cornell University Weill Hall IthacaNY14853 United States Asa Sul Distrito Federal Brasilia70200-660 Brazil

Background: Infusion pumps (IPs) are medical devices used for the continuous and precise delivery of medications or nutrients. Their use has expanded and is now widespread in emergency rooms, ICUs, pediatrics, and other hospital departments. Failures in IPs can lead to adverse events, compromising patient health. In addition to the risks to patients, IPs are the medical devices most frequently associated with reports of adverse events in Brazil, highlighting the need to monitor their operational conditions to minimize failures during use. Results: Thus, the objective of this research is to analyze the reliability of infusion pumps (IPs) in a Brazilian hospital using an internal database from Clinical engineering software. Probability distributions for repair time and time between failures were modeled, and parameters such as reliability and availability were calculated, with a focus on investigating hospital departments with recurring failures. Conclusion: In evaluating the operating equipment, a lack of detail in failure notes and service order openings was observed, which can hinder maintenance planning. The longest repair times were recorded in the ICU (Neurology), which houses the majority of IPs. Graphical analysis and testing demonstrated that the Weibull distribution effectively models both time between failures and repair time. The IP A model showed better results in terms of availability and reliability, thereby improving the security of the IPs. © The Author(s) 2025.

关键词： Weibull distribution

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Improving Mechanical Durability of SLA-Printed Components for Load-Bearing

Improving Mechanical Durability of SLA-Printed Components fo...

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154th Annual Meeting and Exhibition of The Minerals, Metals and Materials Society, TMS 2025

作者： Fani, Niloofar Monfared, Armaghan Hashemi Sadeghzade, Sorour Tavangarian, Fariborz Mechanical Engineering Program School of Science Engineering and Technology Pennsylvania State University Harrisburg MiddletownPA17057 United States Department of Biomedical Engineering Pennsylvania State University State College University ParkPA16802 United States School of Engineering Westlake University Hangzhou310024 China

ISBN: (纸本)9783031807473

This study explored the impact of post-printing parameters in stereolithography (SLA) technology, particularly focusing on how photopolymerization affected the mechanical properties of samples. Building on previous research, the investigation revealed that different curing temperatures significantly influenced the rigidity and stiffness of the printed samples. The mechanical properties of the samples were evaluated through three-point bending tests. Curing at 60 °C left some polymer chains uncured, resulting in less rigid samples but increased load capacity (up to 30 ± 2.4 N) and deflection (2.9 ± 0.6 mm). On the other hand, curing at 70 °C enhanced the rigidity and stiffness, especially for larger samples. The results demonstrated that photopolymerization and the resulting polymer chain cross-linking are crucial for achieving the desired mechanical properties. Notably, as the diameter of the samples decreased, the difference in stiffness between the 60 and 70 °C cured samples also reduced. The findings highlight the importance of optimizing curing temperatures to tailor the mechanical performance of SLA-printed components for specific applications. © The Minerals, Metals & Materials Society 2025.

关键词： Bending tests

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Cell-Instructive Biomaterials with Native-Like Biochemical Complexity

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Annual review of biomedical engineering 2025年第1期27卷 185-209页

作者： Marjan, Tuba Lafuente-Gómez, Nuria Rampal, Akaansha Mooney, David J. Peyton, Shelly R. Qazi, Taimoor H. Weldon School of Biomedical Engineering Purdue University West Lafayette Indiana USA email: tqazi@purdue.edu John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts USA email: mooneyd@seas.harvard.edu Wyss Institute for Biologically Inspired Engineering at Harvard University Boston MA United States Molecular and Cellular Biology Graduate Program University of Massachusetts Amherst MA United States John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts USA email: Department of Chemical Engineering University of Massachusetts Amherst MA United States Department of Biomedical Engineering Tufts University Medford Massachusetts USA email: Weldon School of Biomedical Engineering Purdue University West Lafayette Indiana USA email:

Biochemical signals in native tissue microenvironments instruct cell behavior during many biological processes ranging from developmental morphogenesis and tissue regeneration to tumor metastasis and disease progression. The detection and characterization of these signals using spatial and highly resolved quantitative methods have revealed their existence as matricellular proteins in the matrisome, some of which are bound to the extracellular matrix while others are freely diffusing. Including these biochemical signals in engineered biomaterials can impart enhanced functionality and native-like complexity, ultimately benefiting efforts to understand, model, and treat various diseases. In this review, we discuss advances in characterizing, mimicking, and harnessing biochemical signals in developing advanced engineered biomaterials. An overview of the diverse forms in which these biochemical signals exist and their effects on intracellular signal transduction is also provided. Finally, we highlight the application of biochemically complex biomaterials in the three broadly defined areas of tissue regeneration, immunoengineering, and organoid morphogenesis.

关键词： biomimetic scaffolds cell-adhesive ligands ECM extracellular matrix matricellular matrisome

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Meta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces

Meta-Learning for Generalizable Connectome Modeling Across H...

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IEEE International Symposium on biomedical Imaging

作者： Qinghao Liang Brendan D. Adkinson Dustin Scheinost Department of Biomedical Engineering Yale University New Haven CT Interdepartmental Neuroscience Program Yale University New Haven CT Department of Radiology and Biomedical Imaging Yale School of Medicine New Haven CT Department of Statistics and Data Science Yale University New Haven CT

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Leveraging large-scale neuroimaging datasets to improve predictive modeling in smaller, specialized cohorts is essential for translating research findings into clinical applications. To address this challenge, we propose a meta-learning inspired approach that enhances phenotype prediction by exploiting inter-phenotype correlations across independent datasets, without requiring uniform imaging data processing. By employing mappings derived from a small, independent cohort with data processed using different atlases, we align the data in the meta-training set to the target space of the meta-testing set. This approach eliminates the need for extensive data reprocessing. Evaluation in the UK Biobank dataset shows that our framework significantly improves predictive performance on unseen phenotypes, demonstrating its potential to generalize connectome-based models to small, heterogeneous cohorts.

关键词： Metalearning Neuroimaging Phenotypes Correlation Biological system modeling Predictive models Data processing biomedical imaging

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