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Corrigendum to: Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality and Emotion

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Cerebral cortex (New York, N.Y. : 1991) 2021年第8期31卷 3974页

作者： Ru Kong Jingwei Li Csaba Orban Mert R Sabuncu Hesheng Liu Alexander Schaefer Nanbo Sun Xi-Nian Zuo Avram J Holmes Simon B Eickhoff B T Thomas Yeo Department of Electrical and Computer Engineering ASTAR-NUS Clinical Imaging Research Centre Singapore Institute for Neurotechnology and Memory Networks Program National University of Singapore Singapore. School of Electrical and Computer Engineering Cornell University Ithaca NY USA. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. CAS Key Laboratory of Behavioral Sciences and Research Center for Lifespan Development of Brain and Mind (CLIMB) Institute of Psychology Beijing China. University of Chinese Academy of Sciences Beijing China. Department of Psychology Yale University New Haven CT USA. Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany. Institute of Neuroscience and Medicine Brain & Behaviour (INM-7) Research Center Jülich Jülich Germany. Centre for Cognitive Neuroscience DukeNUS Medical School Singapore. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore.

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Using electropolymerization based doping for electro-addressable functionalization of a multi-electrode array probe for nucleic acid detection

arXiv

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arXiv 2017年

作者： Şen, Mustafa Biomedical Engineering Department Izmir Katip Celebi University Izmir Turkey Biomedical Technologies Graduate Program Izmir Katip Celebi University Izmir Turkey

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Freshwater microalgae-mediated engineered nanoparticles: Sustainable approach for heavy metals remediation

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Bioresource technology 2025年 434卷 132761页

作者： Manish Sutradhar Raju Kumar Sharma Gobinda Dey Uttara Sukul Koyeli Das Md Taharia Pin-Yun Lin Shafiqa Ali Chin-Wen Wang Chien-Yen Chen 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 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 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. Department of Biomedical Sciences Graduate Institute of Molecular Biology 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 Earth and Environmental Sciences National Chung Cheng University 168 University Road Min-Hsiung Chiayi County 62102 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 You-Cheng Engineering & Technology Co. Ltd 168 University Road Min-Hsiung Chiayi Country 62102 Taiwan. Electronic address: yen@eq.ccu.edu.tw.

Recently, convergence of nanotechnology and sustainable approaches has emerged as promising strategy for advanced remediation of heavy metals (HMs) from water. However, engineered nanoparticles (ENPs)-derived from freshwater microalgae gained attention as viable alternative, owing their inherent metal tolerance, rapid-growth rates, and versatile metabolic capabilities. This review predominantly focuses on freshwater microalgae-mediated-ENPs, highlighting intracellular/extracellular pathways induced by biomolecules such as polysaccharides, proteins, lipids, reductases etc., which govern nanoparticle nucleation, stabilization, and functionalization. Subsequently, the review discusses significant types of ENPs including iron, silver, gold, cadmium-sulfide, iron-oxide, nanocomposites, and bio-nano-hybrids nanoparticles, which reported removal efficiency from 21 to 100% of different HMs (lead, cadmium, chromium, copper, zinc, etc.). Despite ENPs exhibit significant potential, their large-scale implementation is constrained by challenges such as scaling-up, nutrient-variability, and high turbidity of wastewater. Future research recommended to focus on optimizing biosynthesis parameters, investigating diverse microalgal-strains, incorporating hybrid nano-materials to enhance their stability, reusability, and scalability for sustainable green-technology.

关键词： Bio-nanotechnology Bioremediation efficiency Environmental nano-materials Green synthesis Heavy metal removal Phytoremediation

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Metatranscriptomics uncovers diurnal functional shifts in bacterial transgenes with profound metabolic effects

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Cell Host & Microbe 2025年

作者： Stephany Flores Ramos Nicole Siguenza Wuling Zhong Ipsita Mohanty Amulya Lingaraju R. Alexander Richter Smruthi Karthikeyan April L. Lukowski Qiyun Zhu Wilhan D.G. Nunes Jasmine Zemlin Zhenjiang Zech Xu Jeff Hasty Pieter C. Dorrestein Satchidananda Panda Rob Knight Amir Zarrinpar Division of Gastroenterology University of California San Diego La Jolla CA USA Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA Department of Pediatrics University of California San Diego La Jolla CA USA Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA Division of Engineering and Applied Science California Institute of Technology Pasadena CA USA Scripps Institution of Oceanography University of California San Diego La Jolla CA USA School of Life Sciences Arizona State University Tempe AZ USA Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA Key Laboratory of Food Science and Technology Nanchang University Nanchang China Shu Chien-Gene Lay Department of Bioengineering University of California San Diego La Jolla CA USA Center for Microbiome Innovation University of California San Diego La Jolla CA USA Synthetic Biology Institute University of California San Diego La Jolla CA USA Salk Institute for Biological Studies La Jolla CA USA Department of Computer Science and Engineering University of California San Diego La Jolla CA USA Halıcıoğlu Data Science Institute University of California San Diego La Jolla CA USA Moores Cancer Center University of California San Diego La Jolla CA USA Division of Gastroenterology Jennifer Moreno Department of Veterans Affairs Medical Center La Jolla CA USA Institute of Diabetes and Metabolic Health University of California San Diego La Jolla CA USA

Diurnal rhythmicity in the gut maintains gut integrity, circadian rhythms, and metabolic homeostasis. However, existing studies focus on microbial composition rather than transcriptional activity. To understand microbial functional dynamics, we characterize diurnal fluctuations in the mouse cecal metatranscriptome and metagenome under high-fat diet and time-restricted feeding (TRF). We show that metatranscriptomics uncovers TRF-induced time-dependent microbial functional shifts that are undetectable with metagenomics alone. We also found bile salt hydrolase ( bsh ) from Dubosiella newyorkensis exhibits diurnal expression in the TRF group. engineering this bsh , along with other candidates, into a native E. coli chassis reveals distinct differences in deconjugation and amidation activities, underscoring functional specificity. In vivo , a D. newyorkensis bsh improves insulin sensitivity, glucose tolerance, and body composition, suggesting a direct role in TRF metabolic benefits. This study highlights how coupling metatranscriptomics with engineered bacterial systems is a powerful approach for uncovering time-dependent bacterial functions related to health and disease.

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Obesity alters pathology and treatment response in inflammatory disease

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四川生理科学杂志 2022年第3期44卷 446-446页

作者： Sagar P Bapat NOMIS Center for Immunobiology and Microbial Pathogenesis The Salk Institute for Biological Studies La Jolla CA USA Gene Expression Laboratory The Salk Institute for Biological Studies La Jolla CA USA Medical Scientist Training Program University of California San Diego La Jolla CA USA Department of Laboratory Medicine University of California San Francisco San Francisco CA USA Department of Microbiology and Immunology University of California San Francisco San Francisco CA USA Diabetes Center University of California San Francisco San Francisco CA USA Medical Scientist Training Program University of California San Francisco CA USA Division of Pulmonary Critical Care Allergy and Sleep Department of Medicine University of California San Francisco San Francisco CA USA School of Pharmaceutical Sciences Xiamen University Xiamen China Department of Dermatology University of California San Diego La Jolla CA USA Department of Surgery University of California San Francisco San Francisco CA USA Department of Medicine University of California San Francisco San Francisco CA USA Sandler Asthma Basic Research Center University of California San Francisco San Francisco CA USA School of Medicine Wake Forest University Winston–Salem NC USA Department of Dermatology Icahn School of Medicine at Mount Sinai New York NY USA Lung Biology Center Department of Medicine University of California San Francisco San Francisco CA USA Department of Biomedical Science Graduate School Kyungpook National University Kyungpook National University Hospital Daegu South Korea Department of Dermatology University of California San Francisco San Francisco CA USA Department of Pathology University of California San Francisco San Francisco CA USA Department of Internal Medicine Division of Pulmonary Critical Care and Sleep Medicine University of Kentucky Lexington KY USA Pulmonary Critical Care Section Department of Medicine Veterans Affairs San Diego Hea

Decades of work have elucidated cytokine signalling and transcriptional pathways that control T cell differentiation and have led the way to targeted biologic therapies that are effective in a range of autoimmune,allergic and inflammatory *** evidence indicates that obesity and metabolic disease can also influence the immune system1-7,although the mechanisms and effects on immunotherapy outcomes remain largely ***,using two models of atopic dermatitis,we show that lean and obese mice mount markedly different immune *** converted the classical type 2 T helper(TH2)-predominant disease associated with atopic dermatitis to a more severe disease with prominent TH17 *** also observed divergent responses to biologic therapies targeting TH2 cytokines,which robustly protected lean mice but exacerbated disease in obese ***-cell RNA sequencing coupled with genome-wide binding analyses revealed decreased activity of nuclear receptor peroxisome proliferator-activated receptor-γ(PPARγ)in TH2 cells from obese mice relative to lean mice.

关键词： dermatitis inflammatory allergic

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Caffeic acid phenethyl ester suppresses EGFR/FAK/Akt signaling, migration, and tumor growth of prostate cancer cells

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Phytomedicine 2023年 116卷

作者： Jen-Chih Tseng Bi-Juan Wang Ya-Pei Wang Ying-Yu Kuo Jen-Kun Chen Tzyh-Chyuan Hour Li-Kuo Kuo Po-Jen Hsiao Chien-Chih Yeh Cheng-Li Kao Li-Jane Shih Chih-Pin Chuu Institute of Cellular and System Medicine National Health Research Institutes Miaoli County 35053 Taiwan Immunology Research Center National Health Research Institutes Miaoli County 35053 Taiwan Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes Miaoli County 35053 Taiwan Neuroscience Research Center Kaohsiung Medical University Kaohsiung 80737 Taiwan Department of Biochemistry School of Medicine Kaohsiung Medical University Kaohsiung 80737 Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung 80737 Taiwan Division of Pulmonary and Critical Care Medicine Department of Internal Medicine Mackay Memorial Hospital Taipei City 104217 Taiwan Department of Nursing Mackay Medical College Taipei City Taiwan Division of Nephrology Department of Internal Medicine Taoyuan Armed Forces General Hospital Taoyuan 325 Taiwan Division of Nephrology Department of Internal Medicine Tri-Service General Hospital National Defense Medical Center Taipei 114 Taiwan Department of Education and Medical Research Taoyuan Armed Forces General Hospital Taoyuan Taiwan Division of Colon and Rectal Surgery Department of Surgery Tri-Service General Hospital National Defense Medical Center Taipei Taiwan Division of Urology Departments of Surgery Tri-Service General Hospital National Defense Medical Center Taipei Taiwan Division of Urology Department of Surgery Taoyuan Armed Forces General Hospital Taoyuan Taiwan Graduate Institute of Medical Science National Defense Medical Center Taipei 114 Taiwan Department of Life Sciences National Central University Taoyuan 32031 Taiwan PhD Program for Aging and Graduate Institute of Basic Medical Science China Medical University Taichung City 40402 Taiwan Biotechnology Center National Chung Hsing University Taichung City 40227 Taiwan

Background Epidermal growth factor receptor (EGFR) is upregulated in prostate cancer (PCa). However, suppression of EGFR did not improve the patient outcome, possibly due to the activation of PI3K/Akt signaling in PCa. Compounds able to suppress both PI3K/Akt and EGFR signaling may be effective for treating advanced PCa. Purpose We examined if caffeic acid phenethyl ester (CAPE) simultaneously suppresses the EGFR and Akt signaling, migration and tumor growth in PCa cells. Methods Wound healing assay, transwell migration assay and xenograft mice model were used to determine the effects of CAPE on migration and proliferation of PCa cells. Western blot, immunoprecipitation, and immunohistochemistry staining were performed to determine the effects of CAPE on EGFR and Akt signaling. Results CAPE treatment decreased the gene expression of HRAS, RAF1, AKT2, GSK3A , and EGF and the protein expression of phospho-EGFR (Y845, Y1069, Y1148, Y1173), phospho-FAK, Akt, and ERK1/2 in PCa cells. CAPE treatment inhibited the EGF-induced migration of PCa cells. Combined treatment of CAPE with EGFR inhibitor gefitinib showed additive inhibition on migration and proliferation of PCa cells. Injection of CAPE (15 mg/kg/3 days) for 14 days suppressed the tumor growth of prostate xenografts in nude mice as well as suppressed the levels of Ki67, phospho-EGFR Y845, MMP-9, phospho-Akt S473, phospho-Akt T308, Ras, and Raf-1 in prostate xenografts. Conclusions Our study suggested that CAPE can simultaneously suppress the EGFR and Akt signaling in PCa cells and is a potential therapeutic agent for advanced PCa.

关键词： Prostate cancer Caffeic acid phenethyl ester Metastasis Epidermal growth factor receptor Fak Akt CAPE caffeic acid phenethyl ester CRPC castration-resistant prostate cancer EGFR epidermal growth factor receptor EMT epithelial-mesenchymal transition GAPDH glyceraldehyde-3-phosphate dehydrogenase mTOR mammalian target of rapamycin PCa prostate cancer PI3K phosphoinositide 3-kinase PSA prostate specific antigen PSMA prostate specific-membrane antigen PTEN phosphatase and tensin homolog

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Phantom Evaluation of a Multi-Pinhole Cardiac SPECT Camera for 3D Molecular Breast Imaging

Phantom Evaluation of a Multi-Pinhole Cardiac SPECT Camera f...

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IEEE Nuclear Science Symposium

作者： Martin P. Tornai Forrest A. McDougal Depts. of Radiology and Biomedical Engineering Medical Physics Graduate Program at Duke University Durham NC Dept. of Radiology at Duke University Medical Physics Graduate Program Durham NC

A tomographic clinical cardiac SPECT system consisting of many static CZT-based pinhole gamma cameras is evaluated for dedicated, pendant 3D molecular breast imaging. The reconstructed spatial resolution and linearity of the spherically symmetric FOV were evaluated with a multi-point source array. A series of anthropomorphic phantom imaging measurements using 0.4 and 0.9 mm diameter lesions was performed;lesion-to-background ratios ranged from [13:1] to [3:1] to simulate various biological uptake;three breasts used were 470-1730 mL in volume. Basic contrast, CNR and coefficient of variation were measured with the anthropomorphic torso+organ background. Decreasing acquisition times from 300-30 sec were a surrogate for lower injected doses. All data was reconstructed using MLEM with various iterations on the commercial workstation. Results indicate that the system largely behaves in the expected way: better overall resolution, linearity, sensitivity, and uniformity closer to the detectors but within the FOV. Other key observations include: (1) higher lesion: background ratios yielded higher image contrast and CNR;(2) lesion contrast and CNR appeared independent of acquisition time;(3) breast size had less of an effect on lesion metrics, but yielded decreased out-of-field (e.g. cardiac and hepatic) contributions with larger breasts. These results indicate that lower injected doses could be utilized for 3D MBI. While additional optimization would be beneficial for breast imaging, this high sensitivity SPECT system could be used for dynamic 3D MBI for lesion diagnostics or therapeutic monitoring.

关键词： Breast Lesions Detectors Single photon emission computed tomography Image reconstruction Image resolution

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Correction to: Comparison of 12 surrogates to characterize CT radiation risk across a clinical population

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European radiology 2021年第10期31卷 8068页

作者： Francesco Ria Wanyi Fu Jocelyn Hoye W Paul Segars Anuj J Kapadia Ehsan Samei Carl E. Ravin Advanced Imaging Labs Duke University Health System 2424 Erwin Road Suite 302 Durham NC 27710 USA. francesco.ria@duke.edu. Clinical Imaging Physics Group Duke University Health System 2424 Erwin Road Suite 302 Durham NC 27710 USA. francesco.ria@duke.edu. Carl E. Ravin Advanced Imaging Labs Duke University Health System 2424 Erwin Road Suite 302 Durham NC 27710 USA. Clinical Imaging Physics Group Duke University Health System 2424 Erwin Road Suite 302 Durham NC 27710 USA. Medical Physics Graduate Program Departments of Radiology Physics Biomedical Engineering and Electrical and Computer Engineering Duke University 2424 Erwin Road Suite 302 Durham NC 27710 USA.

A Correction to this paper has been published: https://***/10.1007/s00330-021-07903-z

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Bioinspired Adhesives: A Phenol‐Amine Superglue Inspired by Insect Sclerotization Process (Adv. Mater. 43/2020)

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Advanced Materials 2020年第43期32卷

作者： Younseon Wang Eun Je Jeon Jeehee Lee Honggu Hwang Seung‐Woo Cho Haeshin Lee Department of Chemistry Korea Advanced Institute of Science and Technology (KAIST) 291 University Rd. Daejeon 34141 Republic of Korea Department of Biotechnology Yonsei University 50 Yonsei‐ro Seoul 03722 Republic of Korea Department of Biomaterials Science and Engineering Yonsei University 50 Yonsei‐ro Seoul 03722 Republic of Korea Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) 291 University Rd. Daejeon 34141 Republic of Korea KONON Advanced Research Cluster KOLON One&Only Tower 110 Magokdong‐ro Seoul 07793 Republic of Korea Center for Nanomedicine Institute for Basic Science (IBS) 50 Yonsei‐ro Seoul 03722 Republic of Korea Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University 50 Yonsei‐ro Seoul 03722 Republic of Korea

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