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Correction to: Biological synthesis and characterization of iron oxide (FeO) nanoparticles using Pleurotus citrinopileatus extract and its biomedical applications

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Biomass Conversion and Biorefinery 2023年第11期14卷 12587-12587页

作者： Manimaran, Kumar Yanto, Dede Heri Yuli Govindasamy, Mani Karunanithi, Bogeshwaran Alasmary, Fatmah Ali Habab, Reem Abdulrahman Research Center for Applied Microbiology National Research and Innovation Agency (BRIN) Cibinong Republic of Indonesia Department of Product Development Institute of Biotechnology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India Faculty International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan Korea University Seongbuk-gu Republic of Korea Department of Research and Innovation Saveetha School of Engineering SIMATS Thandalam India Department of Petroleum Engineering Dhaanish Ahmed College of Engineering Chennai India Department of Chemistry College of Science King Saud University Riyadh Saudi Arabia

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Biologically-induced synthetic manganese carbonate precipitate (BISMCP) for potential applications in heavy metal removal

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Heliyon 2023年第5期9卷

作者： Dewi, Anggraeni Kumala Sharma, Raju Kumar Das, Koyeli Sukul, Uttara Lin, Pin-Yun Huang, Yi-Hsun Lu, Chung Ming Lu, Cheng-Kang Chen, Tsung-Hsien Chen, Chien-Yen Department of Physics National Chung Cheng University University Road Minhsiung Chiayi County 62102 Taiwan Doctoral Program in Science Technology Environment and Mathematics Department of Earth and Environmental Sciences National Chung Cheng University 168 University Road Min-Hsiung Chiayi County 62102 Taiwan Department of Chemistry and Biochemistry National Chung Cheng University 168 University Road Min-Hsiung Chiayi County 62102 Taiwan Department of Biomedical Sciences Graduate Institute of Molecular Biology National Chung Cheng University 168 University Road Min-Hsiung Chiayi County 62102 Taiwan Department of Chemical Engineering National Chung Cheng University University Road Minhsiung Chiayi County 62102 Taiwan Department of Chest Division Internal Medicine Ditmanson Medical Foundation Chiayi Christian Hospital 600566 Taiwan Department of Internal Medicine Ditmanson Medical Foundation Chiayi Christian Hospital 600566 Taiwan Center for Nano Bio-Detection Center for Innovative Research on Aging Society AIM-HI National Chung Cheng University 168 University Road Min-Hsiung Chiayi County 62102 Taiwan

Heavy metal pollution of water is a burning issue of today's world. Among several strategies involved for heavy metal remediation purpose, biomineralization has shown great potential. Of late, research has been focused on developing effective mineral adsorbents with reduced time and cost consumption. In this present paper, the Biologically-Induced Synthetic Manganese Carbonate Precipitate (BISMCP) was produced based on the biologically-induced mineralization method, employing Sporosarcina pasteurii in aqueous solutions containing urea and MnCl₂. The prepared adsorbent was characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), SEM-energy dispersive X-ray spectroscopy (SEM-EDX), X-ray diffraction (XRD) and BET surface area analyzer. EDX analysis showed the elements in the crystal BISMCP were Mn, C, and O. XRD result of BISMCP determined the crystal structure, which is close to rhodochrosite (MnCO₃). Spectral peaks of FTIR at 1641.79 cm⁻¹ confirmed the appearance of C[dbnd]O binding, with strong stretching of CO₃²⁻ in Amide I. From the six kinds of BISMCP produced, sample MCP-6 has the higher specific surface area by BET analysis at 109.01 m²/g, with pore size at 8.76 nm and higher pore volume at 0.178 cm³/g. These specifications will be suitable as an adsorbent for heavy metal removal by adsorption process. This study presents a preliminary analysis of the possibility of BISMCP for heavy metals adsorption using ICP multi-element standard solution XIII (As, Cr, Cd, Cu, Ni, and Zn). BISMCP formed from 0.1 MnCl₂ and 30 ml of bacteria volume (MCP-6) produced a better adsorbent material than others concentrations, with the adsorption efficiency of total As at 98.9%, Cr at 97.0%, Cu at 94.7%, Cd at 88.3%, Zn at 48.6%, and Ni at 29.5%. Future work could be examined its efficiency adsorbing individual heavy metals. © 2023

关键词： Adsorbent material Biologically induced mineralization Biomineralization Heavy metal removal Manganese carbonate (MnCO3) Sporosarcina pasteurii

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Measuring Arterial Stiffness in a Head-Down Tilt Bed Rest Study: A Multisensor Approach*

Measuring Arterial Stiffness in a Head-Down Tilt Bed Rest St...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Stefan Orter Stefan Möstl Martin Bachler Fabian Hoffmann Eugenijus Kaniusas Michaela Reisinger Siegfried Wassertheurer Jens Tank Bernhard Hametner Health & Bioresources Department AIT Austrian Institute of Technology Vienna Austria DLR German Aerospace Center Institute of Aerospace Medicine Cologne Germany Department of Cardiology University Hospital Cologne Cologne Germany Research Group Biomedical Sensing Institute of Electrodynamics Microwave and Circuit Engineering Technical University of Vienna Vienna Austria Center for Technology Experience AIT Austrian Institute of Technology Vienna Austria

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Arterial stiffness is an important indicator for vascular aging and an independent predictor for cardiovascular diseases. During space flights or simulated space flights by prolonged head-down tilt bed rest, major cardiovascular alterations occur. However, the changes in arterial stiffness are not fully understood yet. Thus, we aimed to develop a setup for the measurement of arterial stiffness during prolonged head-down tilt bed rest, which incorporates several combinations of biosignals and measurement locations for the determination of pulse transit times. By performing measurements using this setup on female and male subjects, we intend to deepen the understanding of changes in arterial stiffness during prolonged head-down tilt bed rest. This work describes and visualizes the complete setup as well as our measurement protocols and algorithms used. The result section shows the successful recording of baseline signals before the bed rest study and visualizes the synchronized recordings of pulse waves measured on different sides of the body. Thus, it is feasible to use the presented setup in bed rest studies.

关键词： Pulse measurements biomedical measurement Electrocardiography Synchronization Protocols Distortion measurement Aerospace engineering

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In vivo cancer detection in animal model using hyperspectral image classification with wavelet feature extraction

In vivo cancer detection in animal model using hyperspectral...

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Medical Imaging 2020: biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Ma, Ling Halicek, Martin Fei, Baowei Univ. of Texas at Dallas Dept. of Bioengineering RichardsonTX75080 United States Tianjin University State Key Laboratory of Precision Measurement Technology and Instrument Tianjin300072 China Georgia Inst. of Tech. Emory Univ. Dept. of Biomedical Engineering AtlantaGA United States Medical College of Georgia Augusta University AugustaGA United States Univ. of Texas Southwestern Medical Center Advanced Imaging Research Center DallasTX United States Univ. of Texas Southwestern Medical Center Department of Radiology DallasTX United States

ISBN: (纸本)9781510634015

Hyperspectral imaging (HSI) is a promising optical imaging technique for cancer detection. However, quantitative methods need to be developed in order to utilize the rich spectral information and subtle spectral variation in such images. In this study, we explore the feasibility of using wavelet-based features from in vivo hyperspectral images for head and neck cancer detection. Hyperspectral reflectance data were collected from 12 mice bearing head and neck cancer. Catenation of 5-level wavelet decomposition outputs of hyperspectral images was used as a feature for tumor discrimination. A support vector machine (SVM) was utilized as the classifier. Seven types of mother wavelets were tested to select the one with the best performance. Classifications with raw reflectance spectra, 1-level wavelet decomposition output, and 2-level wavelet decomposition output, as well as the proposed feature were carried out for comparison. Our results show that the proposed wavelet-based feature yields better classification accuracy, and that using different type and order of mother wavelet achieves different classification results. The wavelet-based classification method provides a new approach for HSI detection of head and neck cancer in the animal model. © 2020 SPIE

关键词： Image classification

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Automated CRISPR/Cas9-based genome editing of human pluripotent stem cells using the StemCellFactory

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Cytotherapy 2025年第5期27卷 S36-S37页

作者： Nießing, B. Breitkreuz, Y. Elanzew, A. de Toledo, M.A.S. Vajs, P. Nolden, M. Erkens, F. Wanek, P. Yeung, S. Au Haupt, S. Koenig, N. Peitz, M. Schmitt, R. Zenke, M. Brustle, O. Bioadaptive Production Fraunhofer Institute for Production Technology IPT Aachen Germany Cellomics Unit LIFE&BRAIN GmbH Bonn Germany Institute of Reconstructive Neurobiology University of Bonn Medical Faculty and University Hospital Bonn Bonn Germany Institute for Biomedical Engineering Cell Biology Faculty of Medicine RWTH Aachen University Aachen Germany Helmholtz Institute for Biomedical Engineering RWTH Aachen University Aachen Germany Department of Medicine IV Hematology Oncology and Stem Cell Transplantation RWTH Aachen University Hospital Aachen Germany Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD) Aachen Germany Fraunhofer Institute for Production Technology IPT Aachen Germany Cell Programming Core Facility University of Bonn Medical Faculty Bonn Germany Laboratory for Machine Tools and Production RWTH Aachen University Aachen Germany

Background & AimCRISPR/Cas9 technology is a leading method for efficient gene editing, enabling the creation of isogenic pairs of mutant and control human induced pluripotent stem cells (hiPSCs). While hiPSCs provide valuable opportunities for disease modeling and personalized medicine, challenges remain in distinguishing specific mutation effects from genetic backgrounds. Manual genome editing processes often face scalability and standardization limitations. The StemCellFactory, a modular robotic system, has been developed to automate the reprogramming, expansion, and differentiation of hiPSCs, enhancing the application of CRISPR/Cas9 in research. MethodologyHiPSCs were cultured in StemMACS iPS-Brew XF medium, with daily medium changes and mycoplasma testing. For CRISPR/Cas9 editing, target gene-specific CRISPR-RNA and tracrRNA formed ribonucleoprotein complexes, utilizing an optimized nucleofection protocol. HiPSCs were dissociated, counted, and nucleofected through manual and automated processes. The automated StemCellFactory workflow included cell preparation, nucleofection, and cell seeding, managed by the COPE software for data visualization. Genotyping of polyclonal hiPSCs was performed via Sanger sequencing to assess editing efficiency, with automated isolation of monoclonal colonies conducted using an integrated CellCelector. ResultsThe StemCellFactory successfully integrated a 4D-Nucleofector with a 96-well shuttle device for automated CRISPR/Cas9 editing. Adjustments replaced manual consumables with scalable formats, enhancing efficiency. The CM150 electroporation program yielded high cell viability (83.5%) and indel rates (81.7%). Optimal culture conditions combined Laminin 521 with CloneR-supplemented iPS-Brew medium, supporting hiPSC survival and colony formation. The automated system allowed parallel processing of up to 24 conditions, demonstrating high editing efficiencies, with indel rates exceeding 80% across all tested cell lines, comparable to ma

关键词： Standardization Personalized Medicine COPE

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Hidden figures underlying quality measures: revealing hidden racial inequalities in end-of-life cancer care delivery: a cohort study

The Lancet Regional Health - Americas

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The Lancet Regional Health - Americas 2025年 47卷

作者： Inas S. Khayal John J. Shin Gabriel A. Brooks Amber E. Barnato Ellesse-Roselee Akré Terri Lewinson Amro M. Farid A. James O'Malley The Dartmouth Institute for Health Policy and Clinical Practice Geisel School of Medicine at Dartmouth Lebanon NH 03756 USA Biomedical Data Science Geisel School of Medicine at Dartmouth Lebanon NH 03756 USA Department of Computer Science Dartmouth College Hanover NH 03755 USA Cancer Population Sciences Program Dartmouth Cancer Center Lebanon NH 03756 USA Department of Medicine Dartmouth Hitchcock Medical Center Lebanon NH 03756 USA Section of Palliative Care Department of Medicine Dartmouth Hitchcock Medical Center Lebanon NH 03756 USA Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Baltimore MD 21205 USA Department of Systems Engineering School of Engineering and Science Stevens Institute of Technology Hoboken NJ 07030 USA Department of Mathematics Dartmouth College Hanover NH 03755 USA

Background Calls for healthcare systems to reduce disparities in cancer care access and outcomes draw on comparisons of existing measures across race and ethnicity subgroups. This approach may hide inequities driven by systematic bias in the timing of care delivery. The goals of this study were to: (1) identify differences in the timing of care delivery between racial groups, and (2) determine whether these differences could be identified from quality measures. Methods Retrospective decedent follow-back study of hospitals treating Medicare fee-for-service beneficiaries with advanced cancer aged 65–99 who died April–December 2016. Among hospitals serving at least 11 decedents of color (including Black or African-American, Asian/Pacific Islander, Hispanic, American Indian/Alaska Native, and Other) and 11 White decedents, we calculated hospital-level differences between White decedents and decedents of color for 1) any use of palliative care and hospice (Measures) and 2) daily counts of palliative care and hospice use for each day in the 6 months before death (Signatures). Findings The cohort included 30,319 decedents across 217 hospitals, of whom 7,852 (25.9%) were people of color (POC). The median of the hospital-specific aggregate measure difference was −5.35% (IQR = 12.83) for palliative care, indicating more POC received any palliative care, and 3.66% (IQR = 12.45) for hospice care, indicating more White people (WP) received any hospice care. We identified 5 high-level cluster-group descriptions of inequality from signatures. Inequality information from signatures matched those from measures in only 46.5% and 39.2% of hospitals for palliative and hospice care, respectively. Interpretation Signatures incorporating timing of care delivery using longitudinal data revealed patterns of racial-ethnic inequalities in end-of-life cancer care otherwise missed by traditional aggregate quality measures. Funding This work was supported by the American Cancer Society Award (RS

关键词： Racial/ethnic healthcare inequities Palliative care Hospice care Healthcare quality indicators

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WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

arXiv

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arXiv 2021年

作者： Luo, Xiangde Liao, Wenjun Xiao, Jianghong Chen, Jieneng Song, Tao Zhang, Xiaofan Li, Kang Metaxas, Dimitris N. Wang, Guotai Zhang, Shaoting School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Department of Radiation Oncology Sichuan Cancer Hospital and Institute Sichuan Cancer Center Chengdu China Department of Radiation Oncology Cancer Center West China Hospital Sichuan University Chengdu China Shanghai Artificial Intelligence Laboratory Shanghai China School of Medicine University of Electronic Science and Technology of China Chengdu China Department of Computer Science Johns Hopkins University Baltimore United States SenseTime Research Shanghai China West China Hospital-SenseTime Joint Lab West China Biomedical Big Data Center Sichuan University Chengdu China Department of Computer Science Rutgers University PiscatawayNJ United States

Whole abdominal organ segmentation is important in diagnosing abdomen lesions, radiotherapy, and follow-up. However, oncologists’ delineating all abdominal organs from 3D volumes is time-consuming and very expensive. Deep learning-based medical image segmentation has shown the potential to reduce manual delineation efforts, but it still requires a large-scale fine annotated dataset for training, and there is a lack of large-scale datasets covering the whole abdomen region with accurate and detailed annotations for the whole abdominal organ segmentation. In this work, we establish a new large-scale Whole abdominal ORgan Dataset (WORD) for algorithm research and clinical application development. This dataset contains 150 abdominal CT volumes (30495 slices). Each volume has 16 organs with fine pixel-level annotations and scribble-based sparse annotations, which may be the largest dataset with whole abdominal organ annotation. Several state-of-the-art segmentation methods are evaluated on this dataset. And we also invited three experienced oncologists to revise the model predictions to measure the gap between the deep learning method and oncologists. Afterwards, we investigate the inference-efficient learning on the WORD, as the high-resolution image requires large GPU memory and a long inference time in the test stage. We further evaluate the scribble-based annotation-efficient learning on this dataset, as the pixel-wise manual annotation is time-consuming and expensive. The work provided a new benchmark for the abdominal multi-organ segmentation task, and these experiments can serve as the baseline for future research and clinical application development. © 2021, CC BY.

关键词： Large dataset

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Exploring Molecular Mechanisms of Cosolvent Enhanced Biomass Deconstruction: An Overview of Recent Progress

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ACS Symposium Series 2019年 1338卷 103-117页

作者： Mostofian, Barmak Petridis, Loukas Cai, Charles M. Department of Biomedical Engineering School of Medicine Oregon Health and Science University PortlandOR97239 United States UT/ORNL Center for Molecular Biophysics Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Biochemistry and Cellular and Molecular Biology University of Tennessee KnoxvilleTN37966 United States Center for Environmental Research and Technology Bourns College of Engineering University of California Riverside 1084 Columbia Avenue RiversideCA92507 United States Center for Bioenergy Innovation Oak Ridge National Laboratory Oak RidgeTN37831 United States

In this chapter, we explore the mechanisms driving efficient thermochemical deconstruction and fractionation of lignocellulosic biomass in cosolvent mixtures for the production of biofuels and bioproducts. New approaches that combine molecular dynamics simulations with experimental characterization highlight the important role of cosolvents and their influence on molecular processes relevant to overcoming the natural recalcitrance of lignocellulose. From localized phase behavior on cellulose fibers to changes in lignin conformation, insights into cosolvent effects on biomass deconstruction involve understanding complex interactions between the solvent-solvent, solvent-substrate, and solvent-catalyst. Recently coordinated research efforts at multiple scales using computational tools, nano-scale imaging, and kinetic models have significantly advanced identification of high-performance cosolvents, shedding light on the mechanisms behind solvent-biomass interactions. Specifically, multifunctional cosolvents have been employed in leading biomass "solvolysis" technologies that favorably coordinate with dilute acids to solubilize and depolymerize all three primary biomass fractions of biomass: cellulose, hemicellulose, and lignin. As a result, recent work in studying solvent effects of multifunctional cosolvents has led to a paradigm shift toward the use of first principles to design biomass deconstruction techniques with the aim of maximizing total carbon utilization in biomass. The synergistic pairing of cosolvents with biomass deconstruction will lead scientists and engineers to overcome key technical and economic barriers of biomass processing, enabling a successful transition of the current energy landscape toward a future bioeconomy based on biomass as an alternative to petroleum. © 2019 American Chemical Society.

关键词： Solvents

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Erratum to “Ros-responsive nanocomposite scaffolds for sustained releasing puerarin to achieve chondroprotection in OA rats” [Mater. Des. 233 (2023) 112214]

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Materials & Design 2024年 244卷

作者： Depeng Fang Zainen Qin Li Zheng Pek Yin Michelle Yew Xianfang Jiang Dan Kai Fangming Song Jinmin Zhao Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration The First Affiliated Hospital of Guangxi Medical University Guangxi Medical University Nanning 530021 China Guangxi Key Laboratory of Regenerative Medicine Guangxi Collaborative Innovation Center of Regenerative Medicine and Medical Bioresource Development and Application The First Affiliated Hospital of Guangxi Medical University Nanning 530021 China Department of Biomedical Engineering Faculty of Engineering National University of Singapore Singapore 117583 Singapore Institute of Materials Research and Engineering Agency for Science Technology and Research (A*STAR) 2 Fusionopolis Way Innovis #08-03 138634 Singapore Guangxi Key Laboratory of Oral and Maxillofacial Rehabilitation and Reconstruction College of Stomatology Hospital of Stomatology Guangxi Medical University Nanning 530021 China Institute of Sustainability for Chemicals Energy and Environment (ISCE2) Agency for Science Technology and Research (A*STAR) 2 Fusionopolis Way Innovis #08-03 138634 Singapore Department of Orthopedics Trauma and Hand Surgery The First Affiliated Hospital of Guangxi Medical University Guangxi Medical University Nanning 530021 China

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Alleviating class-wise gradient imbalance for pulmonary airway segmentation

arXiv

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arXiv 2020年

作者： Zheng, Hao Qin, Yulei Gu, Yun Xie, Fangfang Yang, Jie Sun, Jiayuan Yang, Guang-Zhong Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong Univeristy Shanghai China School of Biomedical Engineering Shanghai Jiao Tong Univeristy Shanghai China Department of Respiratory and Critical Care Medicine Department of Respiratory Endoscopy Shanghai Chest Hospital Shanghai Engineering Research Center of Respiratory Endoscopy Shanghai China

— Automated airway segmentation is a prerequisite for pre-operative diagnosis and intra-operative navigation for pulmonary intervention. Due to the small size and scattered spatial distribution of peripheral bronchi, this is hampered by a severe class imbalance between foreground and background regions, which makes it challenging for CNN-based methods to parse distal small airways. In this paper, we demonstrate that this problem is arisen by gradient erosion and dilation of the neighborhood voxels. During back-propagation, if the ratio of the foreground gradient to background gradient is small while the class imbalance is local, the foreground gradients can be eroded by their neighborhoods. This process cumulatively increases the noise information included in the gradient flow from top layers to the bottom ones, limiting the learning of small structures in CNNs. To alleviate this problem, we use group supervision and the corresponding WingsNet to provide complementary gradient flows to enhance the training of shallow layers. To further address the intra-class imbalance between large and small airways, we design a General Union loss function that obviates the impact of airway size by distance-based weights and adaptively tunes the gradient ratio based on the learning process. Extensive experiments on public datasets demonstrate that the proposed method can predict the airway structures with higher accuracy and better morphological completeness than the baselines. Copyright © 2020, The Authors. All rights reserved.

关键词： Erosion

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