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Skeletal interoception and prospective application in biomaterials for bone regeneration

Bone Research 2025年第1期13卷 1-14页

作者： Long Bai Jilong Li Guangfeng Li Dongyang Zhou Jiacan Su Changsheng Liu Organoid Research Center Institute of Translational MedicineShanghai UniversityShanghaiChina National Center for Translational Medicine(Shanghai)SHU Branch Shanghai UniversityShanghaiChina Wenzhou Institute of Shanghai University WenzhouZhejiangChina Department of Orthopedics Shanghai Zhongye HospitalShanghaiChina Department of Orthopedics Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina Key Laboratory for Ultrafine Materials of Ministry of Education Engineering Research Center for Biomedical Materials of the Ministry of EducationEast China University of Science and TechnologyShanghaiChina

Accumulating research has shed light on the significance of skeletal interoception,in maintaining physiological and metabolic homeostasis related to bone *** review provides a comprehensive analysis of how skeletal interoception influences bone homeostasis,delving into the complex interplay between the nervous system and skeletal *** key focus of the review is the role of various factors such as prostaglandin E2(PGE2)in skeletal health via skeletal *** explores how nerves innervating the bone tissue communicate with the central nervous system to regulate bone remodeling,a process critical for maintaining bone strength and ***,the review highlights the advancements in biomaterials designed to utilize skeletal interoception for enhancing bone regeneration and treatment of bone *** biomaterials,tailored to interact with the body’s interoceptive pathways,are positioned at the forefront of innovative treatments for conditions like osteoporosis and *** represent a convergence of bioengineering,neuroscience,and orthopedics,aiming to create more efficient and targeted therapies for bone-related *** conclusion,the review underscores the importance of skeletal interoception in physiological regulation and its potential in developing more effective therapies for bone *** emphasizes the need for further research to fully understand the mechanisms of skeletal interoception and to harness its therapeutic potential fully.

关键词： homeostasis biomaterials utilize

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Non-Hermitian Physics in Mesoscopic Electron Transport Through Coupled Quantum Dots

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Chinese Physics Letters 2025年第4期42卷 114-124页

作者： Yiyang Li Jincheng Lu Chen Wang Jian-Hua Jiang School of Physical Science and Technology&Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow UniversitySuzhou215006China Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions School of Physical Science and TechnologySuzhou University of Science and TechnologySuzhou215009China Advanced Technology Research Institute of Taihu Photon Center School of Physical Science and TechnologySuzhou University of Science and TechnologySuzhou 215009China Department of Physics Zhejiang Normal UniversityJinhua321004China School of Biomedical Engineering Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou215123China School of Physical Sciences University of Science and Technology of ChinaHefei 230026China

We investigate electron mesoscopic transport in a three-terminal setup with coupled quantum dots and a magnetic *** mapping the original transport problem into a non-Hermitian Hamiltonian form,we study the interplay between the coherent couplings between quantum dots,the magnetic flux,and the dissipation due to the tunnel coupling with the reservoirs.

关键词： quantum dots magnetic fluxby electron mesoscopic transport non hermitian physics magnetic fluxand coherent couplings transport problem tunnel coupling

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Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification

arXiv

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arXiv 2025年

作者： Thompson, Jordan Koe, Ronald Le, Anthony Goodman, Gabriella Brown, Daniel S. Kuntz, Alan Robotics Center Kahlert School of Computing University of Utah Salt Lake CityUT84112 United States Department of Biomedical Engineering University of Utah United States

Autonomous surgical robots are a promising solution to the increasing demand for surgery amid a shortage of surgeons. Recent work has proposed learning-based approaches for the autonomous manipulation of soft tissue. However, due to variability in tissue geometries and stiffnesses, these methods do not always perform optimally, especially in out-of-distribution settings. We propose, develop, and test the first application of uncertainty quantification to learned surgical soft-tissue manipulation policies as an early identification system for task failures. We analyze two different methods of uncertainty quantification, deep ensembles and Monte Carlo dropout, and find that deep ensembles provide a stronger signal of future task success or failure. We validate our approach using the physical daVinci Research Kit (dVRK) surgical robot to perform physical soft-tissue manipulation. We show that we are able to successfully detect task failure and request human intervention when necessary while still enabling autonomous manipulation when possible. Our learned tissue manipulation policy with uncertainty-based early failure detection achieves a zero-shot sim2real performance improvement of 47.5% over the prior state of the art in learned soft-tissue manipulation. We also show that our method generalizes well to new types of tissue as well as to a bimanual soft-tissue manipulation task. Copyright © 2025, The Authors. All rights reserved.

关键词： Robotic surgery

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Correction to: A pro-healing short-chain antimicrobial peptide that inhibits sepsis (Science China Materials, (2024), 67, 11, (3727-3741), 10.1007/s40843-024-3002-0)

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Science China Materials 2025年第6期68卷 2157-2160页

作者： Ren, Zekai Ding, Xin Wang, Yumei Wu, Han Liu, Xin Cao, Yang Cong, Hailin Shen, Youqing Yu, Bing College of Chemistry and Chemical Engineering College of Materials Science and Engineering Institute of Biomedical Materials and Engineering Qingdao University Qingdao266071 China State Key Laboratory of Bio-Fibers and Eco-Textiles Qingdao University Qingdao266071 China School of Materials Science and Engineering Shandong University of Technology Zibo255000 China Key Laboratory of Biomass Chemical Engineering of Ministry of Education Center for Bionanoengineering and Department of Chemical and Biological Engineering Zhejiang University Hangzhou310027 China

In the version of article originally published in the volume 67, 2024 of Sci China Mater (pages 3733, 3735, 3736, https://***/ 10.1007/s40843-024-3002-0), three minor errors appeared in the original article, all of which were caused by incorrect placement of images during the layout process. The corrected Fig. 1g, Fig. 3b, and Fig. 4a are as follows. These corrections do not change or affect the results or conclusions of this article. All authors agree with these corrections and sincerely. © Science China Press 2025.

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Classification of the Heartbeats in Electrocardiograms with K-Nearest Neighbors Algorithm, Random Forests, and Support Vector Machines - A Pilot Study 21st

Classification of the Heartbeats in Electrocardiograms with ...

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21st Scientific Conference on Medical and Sport Technologies, 2024

作者： Vural, Muzaffer Samed Heryan, Katarzyna Sieciński, Szymon Bilko, Pawel Grzegorzek, Marcin Faculty of Automatic Control Electrical Engineering and Biomedical Engineering Department of Measurement and Electronics AGH University of Science and Technology Aleja Adama Mickiewicza 30 Kraków30-059 Poland Institute of Medical Informatics University of Lübeck Ratzeburger Allee 160 Lübeck23562 Germany Faculty of Biomedical Engineering Department of Medical Informatics and Artificial Intelligence Silesian University of Technology Franklina Delano Roosevelta 40 Zabrze41-800 Poland Department of Clinical Engineering Academy of Silesia Rolna 43 Katowice40-555 Poland German Research Center for Artificial Intelligence Ratzeburger Allee 160 Lübeck23562 Germany

ISBN: (纸本)9783031821424

Electrocardiography (ECG) is vital for diagnosing and monitoring cardiovascular diseases. Automatic interpretation of ECG signals, particularly classifying heartbeats, is essential in diagnosing these conditions. We compared the performance of three classifiers (K-Nearest Neighbors (KNN), Random Forests (RF), and Support Vector Machine (SVM)) using heartbeat and ECG signal features. We trained the classifiers on 173 heartbeats from 11 recordings in the MIT-BIH Arrhythmia (MITDB) Database. To address imbalance, we used SMOTE (Synthetic Minority Over-sampling Technique) to increase the number of abnormal heartbeats. We divided the data into 70% for training set and 30% for testing set, evaluating performance through 10-fold cross-validation. Results demonstrated state-of-the-art performance for KNN, RF, and SVM. KNN achieved an overall accuracy, positive predictive value, and sensitivity of 0.977, 0.978, and 0.978, respectively. RF achieved an overall accuracy, precision, and sensitivity of 0.971, 0.972, and 0.971, respectively. SVM achieved a recall of 0.988, 0.989, and 0.988. SVM exhibited the highest overall performance in heartbeat classification (0.99), followed by KNN (0.98) and RF (0.97). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Support vector machines

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Fighting hypoxia to improve photodynamic therapy-driven immunotherapy:Alleviating,exploiting and disregarding

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Chinese Chemical Letters 2025年第2期36卷 29-40页

作者： Liangliang Jia Ye Hong Xinyu He Ying Zhou Liujiao Ren Hongjun Du Bin Zhao Bin Qin Zhe Yang Di Gao The Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and TechnologyXi'an Jiaotong UniversityXi'an 710049China Center of Digestive Endoscopy Shaanxi Provincial Cancer HospitalXi'an 710061China Research Institute of Xi'an Jiaotong University Hangzhou 311200China Department of Gastroenterology Second Affiliated HospitalXi'an Jiaotong UniversityXi'an 710004China Department of Ophthalmology Xijing HospitalXi'an 710032China Department of Epidemiology Shaanxi Provincial Cancer HospitalXi'an 710061China

Innovative anti-cancer therapies that activate the immune system show promise in combating cancers resistant to conventional *** therapy(PDT)is one such treatment,which not only directly eliminates tumor cells but also functions as an in situ tumor vaccine by enhancing tumor immunogenicity and triggering anti-tumor immune responses through immunogenic cell death(ICD).However,the effectiveness of PDT in enhancing immune responses is influenced by factors,such as photosensitizers and the tumor microenvironment,particularly *** clinically used PDT heavily relies on oxygen(O_(2))availability and can be limited by tumor ***,the tumor immunosuppressive microenvironment induced by hypoxia affects the anti-tumor immunity of tumor-infiltrating effector T ***,the immunosuppressive myeloid-lineage cells are recruited to the hypoxic tumor tissue and exhibit higher immunosuppressive capabilities under hypoxia ***,numerous strategies have been developed to modulate tumor hypoxia or to create hypoxia-compatible PDT,aiming to reduce the effects of tumor hypoxia on PDT-driven *** review investigates these strategies,including approaches to alleviate,exploit,and disregard tumor hypoxia within the context of PDT/*** also emphasizes the role of advanced nanomedicine and its benefits in these strategies,while outlining current challenges and future prospects in the field.

关键词： Photodynamic therapy Tumor hypoxia Immunotherapy Immunogenic cell death Photosensitizers Nanomedicine

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An Integrated Experimental and Modeling Approach for Crystallization of Complex Biotherapeutics

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Crystal Growth & Design 2025年第11期25卷 3687-3696页

作者： Vivekananda Bal Moo Sun Hong Jacqueline M. Wolfrum Paul W. Barone Stacy L. Springs Anthony J. Sinskey Robert M. Kotin Richard D. Braatz Department of Chemical Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States School of Chemical and Biological Engineering Seoul National University Seoul 08826 Republic of Korea Center for Biomedical Innovation Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States Center for Biomedical Innovation Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States；Department of Biology Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States Center for Biomedical Innovation Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States；Gene Therapy Center University of Massachusetts Chan Medical School Worcester Massachusetts 01655 United States Department of Chemical Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States；Center for Biomedical Innovation Massachusetts Institute of Technology Cambridge Massachusetts 02139-4307 United States

Crystallization of proteins, specifically proteins of medical relevance, is performed for various reasons, such as to understand the protein structure and to design therapies. Obtaining kinetic constants in rate laws for nucleation and growth of advanced biotherapeutics such as capsids, an assembly of macromolecules, is challenging and essential to the design of crystallization processes. In this work, coupled population balance and species balance equations are developed to extract nucleation and growth kinetics for the crystallization of recombinant adeno-associated virus (rAAV) capsids. A comparison of model results with that of experimental data for capsid crystallization in a hanging-drop vapor diffusion system shows that the slow rate of vapor diffusion from the droplet controls the initial nucleation and growth processes, and the capsid nucleation occurs via heterogeneous nucleation in the microdroplet. Results also show that the capsids, which are of very high molecular weight (∼3.6 MDa), have a similar tendency to nucleate as small organic molecules such as glycine (∼75 Da), low-molecular-weight proteins, and small-molecule active pharmaceutical ingredients due to their ball-shaped outer structure/shape. Capsids also show a prolonged nucleation period as for proteins and other macromolecules but have a slow growth rate with a growth rate prefactor seven orders of magnitude smaller than that of lysozyme. The capsid crystal growth rate is weakly sensitive to supersaturation compared to lysozyme and is limited by the transport of capsids due to slow Brownian motion resulting from the very high molecular *** developed a mathematical model based on population balance equation and compared the simulation results with the in-house experimental measurements for temporal evolution of crystal growth rate, crystal size distribution, total number density, total length, total radius, total surface area, and total volume.

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Computational Analysis of Intravascular OCT Images for Future Clinical Support: A Comprehensive Review

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IEEE Reviews in biomedical engineering 2025年 PP卷 PP页

作者： Lee, Juhwan Gharaibeh, Yazan Dong, Pengfei Dallan, Luis A. P. Pereira, Gabriel T. R. Kim, Justin N. Hoori, Ammar Gu, Linxia Bezerra, Hiram G. Cortese, Bernardo Wilson, David L. Case Western Reserve University Department of Biomedical Engineering ClevelandOH United States The Hashemite University Department of Biomedical Engineering Zarqa Jordan Florida Institute of Technology Department of Biomedical Engineering and Sciences MelbourneFL United States University Hospitals Cleveland Medical Center Harrington Heart and Vascular Institute ClevelandOH United States University of South Florida Heart and Vascular Institute TampaFL United States Case Western Reserve University Department of Biomedical Engineering and Radiology ClevelandOH United States

Over the past two decades, intravascular optical coherence tomography (IVOCT) has emerged as a promising tool for planning percutaneous coronary interventions (PCI), studying coronary artery disease, and assessing treatments. With its nearhistological resolution and optical contrast, IVOCT uniquely evaluates coronary plaque characteristics, enhancing the guidance of interventional procedures. Artificial intelligence (AI) techniques have been widely applied to IVOCT imaging, providing fast and accurate automated interpretation. These techniques hold significant potential for both clinical and research purposes. Clinically, automated analysis offers comprehensive assessments of coronary plaques, leading to better treatment decisions during PCI. For research, automated interpretation of IVOCT opens new avenues to understand the pathophysiology of coronary atherosclerosis. However, these techniques face several limitations, including issues related to spatial resolution, challenges in manual assessments, and the additional time required for these analyses. This review covers recent advancements and applications of AI techniques and computational simulation methods in IVOCT image analysis, including vessel wall segmentation, plaque characterization, stent analysis, and their clinical applications. Furthermore, we discuss the potential of AI-enhanced IVOCT analysis to facilitate personalized decision-making, potentially improving short- and long-term patient outcomes. © 2008-2011 IEEE.

关键词： Optical coherence tomography

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Strategic Study on the Development of Inorganic Non-metallic Biomaterials

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Wuji Cailiao Xuebao/Journal of Inorganic Materials 2025年第5期40卷 449-456页

作者： Chen, Xi Yuan, Yuan Tan, Yeqiang Liu, Changsheng Engineering Research Center for Biomedical Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology Shanghai200237 China Department of Engineering and Materials Science National Natural Science Foundation of China Beijing100085 China

Inorganic non-metallic biomaterial is one of main types of biomaterials, which is widely used in biomedical fields such as tissue repair, tumor therapy, and drug delivery., making an important contribution to national life and health. Research on inorganic non-metallic biomaterials in China is flourishing, but their production and application are still in the stage of overcoming difficulties. To realize the high-quality development of China's inorganic non-metallic biomaterials and improve their hard power to protect national life and health, this paper analyzes hotspots and difficult problems in research and application of China's inorganic non-metallic biomaterials by means of strategic study. Based on current development opportunities and challenges, some suggestions are proposed for the development of inorganic non-metallic biomaterials, such as material design for unique performance, research on materiobiology, exploration of new principles and mechanisms mediated by materials, customization by intelligent personalization, design through big data screening and artificial intelligence, and standardization based evaluation/regulation. This aims to provide guidance for development of inorganic non-metallic biomedical products and push forward scientific research while accumulating talent resources. © 2025 Science Press. All rights reserved.

关键词： Binary alloys

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On the Variation of Intercalation Voltage in Si-doped (Na3+yV2(PO4)3-y(SiO4) y) Cathode Material: A First-Principles Study

On the Variation of Intercalation Voltage in Si-doped (Na3+y...

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2024 International Conference on Physics and technology of Advanced Materials, ICPTAM 2024

作者： Scientika, Qory Cipta Wella, Sasfan Arman Fathurrahman, Fadjar Nuruddin, Ahmad Anshori, Isa Sakti, Aditya Wibawa Shukri, Ganes Nano and Quantum Technology Research Group Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia South Tangerang Indonesia Bandung Institute of Technology Bandung Indonesia Lab-on-Chip Laboratory Biomedical Engineering Department Bandung Institute of Technology Indonesia Global Center for Science and Engineering Waseda University Tokyo Japan

The Na3V2(PO4)3 (i.e. NVP) is a Natrium Super-ionic Conductor (NaSICON) type compound which provides a 3D open framework that has strong covalent bonds, making this material a promising cathode material with high-power density. Increasing its ability to deliver Sodium-ion at a faster rate and at a higher electronic conductivity have been becoming target researches for its further utilization. Here, by utilizing the first-principles calculation, we investigated the effect of partial substitution of P with Si on the intercalation voltage of silicon-doped NVP. We determine the thermodynamically stable phase of the pristine NVP and Si-doped NVP or Na3.1V2(PO4)2.9(SiO4)0.1 (i.e. NVPS0.1) by considering various sodium configurations. Based on the mixing energy results, we then calculated the intercalation voltage and found that the addition of Si dopant slightly increases the range of intercalation voltage of pure NVP from 1.43-2.36 V, ∆V = 0.93 V and 1.24-2.44 V for NVPS0.1 with ∆V = 1.20 V, increases 0.27 V. In general, our finding shows the potential of Si to modulate the overall intercalation voltage window of a NVP-based cathode material for Na-ion battery. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Sodium-ion batteries

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