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SSRN 2022年

作者： Fan, Lingzhi Wu, Jianbing Yang, Jing Li, Fugang Yan, Wannian Tan, Fei Zhang, Madeline Draz, Mohamed S. Han, Huanxing Zhang, Pengfei Department of Central Laboratory Shanghai Skin Disease Hospital School of Medicine Tongji University Shanghai200443 China Key Laboratory of Drug Preventation and Control Technology of Zhejiang Province Zhejiang Police College Hangzhou China Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and Technology Xi’an Jiaotong University Xi’an710049 China Shanghai Upper Biotech Co Ltd Shanghai201201 China Department of Medicine Case Western Reserve University School of Medicine ClevelandOH44106 United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Department of Pharmacy Changzheng Hospital the Second Military Medical University Shanghai200433 China

Point-of-care test (POCT) allows for rapid and sensitive screening of drugs of abuse. However, traditional gold nanoparticle-based lateral flow immunoassay strip is not sensitive enough for detection of trace drugs in hair samples. Herein, we aimed to develop a more specific system using a composite polymer nanobead that is deeply dyed with oil soluble dyes, and termed as deeply dyed nanobead (DDNB). The prepared composite nanobeads displayed a clear core-shell structure and the core/shell ratios were readily controlled by polymer/dye feeding ratios. The absorbance stable nanobeads capped with carboxyl groups were covalently conjugated with antibodies, and were employed for preparation of lateral flow immunoassay strips for sensitive detection of drugs in hair with naked eye. The developed drug strips allow the detection of drugs such as morphine and methamphetamine in hair samples within 13 min (including hair sample processing ~5 min). The cut-off value of DDNB strip for methamphetamine detection with naked eye is down to concentration of 8.0 ng/mL, which is about 3.1 times more sensitive than the traditional gold nanoparticles based lateral flow immunoassay. Moreover, the colorful DDNB system has the potential for multiplexing detection of analytes at point-of-care settings and low cost. © 2022, The Authors. All rights reserved.

关键词： Metal nanoparticles

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Author Correction: Inferring time-varying generation time, serial interval, and incubation period distributions for COVID-19 ( doi 10.1038/s41467-022-35496-8, 13 dec 2022 )

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NATURE COMMUNICATIONS 2023年第1期14卷 1-1页

作者： Chen, Dongxuan Lau, Yiu-Chung Xu, Xiao-Ke Wang, Lin Du, Zhanwei Tsang, Tim K. Wu, Peng Lau, Eric H. Y. Wallinga, Jacco Cowling, Benjamin J. Ali, Sheikh Taslim WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public Health Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong Special Administrative Region China Laboratory of Data Discovery for Health Limited Hong Kong Science and Technology Park New Territories Hong Kong Special Administrative Region China College of Information and Communication Engineering Dalian Minzu University Dalian 116600 China Department of Genetics University of Cambridge Cambridge CB2 3EH UK Center for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands

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The Associations between Lung Cancer Incidence and Long-Term Exposure to Fine Particulate Matterand its Constituents

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SSRN 2024年

作者： Hu, Jinlong Yang, Lei Kang, Ning Wang, Ning Zhang, Xi Liu, Shuo Li, Huichao Xue, Tao Ji, Jia-Fu Zhu, Tong College of Environmental Sciences and Engineering Peking University Beijing China Key Laboratory of Carcinogenesis and Translational Research Ministry of Education/Beijing Beijing Office for Cancer Prevention and Control Peking University Cancer Hospital & Institute Beijing100142 China Peking University Cancer Hospital Affiliated Cancer Hospital of Inner Mongolia Medical University Inner Mongolia Cancer Center Inner Mongolia Campus Hohhot010020 China Institute of Reproductive and Child Health National Health Commission Key Laboratory of Reproductive Health Department of Epidemiology and Biostatistics Ministry of Education Key Laboratory of Epidemiology of Major Diseases PKU School of Public Health Peking University Health Science Centre Beijing China Advanced Institute of Information Technology Peking University Hangzhou China State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management Center for Environment and Health Peking University Beijing China Department of Gastrointestinal Surgery III China

Background: Associations between long-term exposure to ambient fine particulate matter (PM2.5) and the incidence of lung cancer are well-known, but the roles of individual PM2.5 constituents [black carbon (BC), ammonium (NH4+), nitrate (NO3−), organic matter (OM), and inorganic sulfate (SO42−)] remain unclear. This study aims to specify the associations between PM2.5 constituents and lung cancer ***: Based on a prospective cohort of 142,980 people in Beijing, a Cox proportional hazards model was utilized to explore possible linear associations of the mass concentrations of PM2.5 and its constituents with lung cancer incidence. We also used weighted quantile sum (WQS), quantile-based g-computation (Qgcomp), and SHapley Additive exPlanations (SHAP) methods to specify the impacts of various exposure ***: Increased concentrations of PM2.5 and its five constituents were significantly associated with an increased incidence of lung cancer. The hazard ratios (HRs) and 95% confidence intervals (CIs) per 1-μg/m3 increase in the 5-year average concentrations were 1.01 (95% CI: 1.00, 1.02) for PM2.5, 1.23 (95% CI: 1.06, 1.42) for BC, 1.15 (95% CI: 1.04, 1.27) for NH4+, 1.08 (95% CI: 1.02, 1.16) for NO3−, 1.04 (95% CI: 1.01, 1.06) for OM, and 1.08 (95% CI: 1.03, 1.15) for SO42−. BC was robustly identified as the key constituent that explained the association between PM2.5 and lung cancer: both the WQS and Qgcomp models assigned the highest weight to BC (WQS weight: 60%, and Qgcomp positive weight: 48%). On SHAP analysis using a random forest model, BC exhibited the second-highest feature importance score (0.021).Conclusions: Using a prospective cohort, this study showed significant associations of lung cancer with PM2.5 and its constituents. The chemical profile affected the carcinogenicity of PM2.5. Reduction of BC by controlling its sources, such as fossil fuel usage and biomass burning, would effectively prevent PM2.5-related lung cancer. © 2024, Th

关键词： Additives

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3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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Assessing the Potential of GPT-4 to Annotate medical Notes Across Different Languages and Countries: A Model Evaluation Study

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SSRN 2024年

作者： Saad Menezes, Maria Clara Hoffman, Alexander F. Tan, Amelia L.M. Nalbandyan, Mariné Omenn, Gilbert S. Mazzotti, Diego R. Hernández-Arango, Alejandro Visweswaran, Shyam Venkatesh, Shruthi Mandl, Kenneth D. Bourgeois, Florence T. Lee, James W.K. Makmur, Andrew Hanauer, David A. Semanik, Michael G. Kerivan, Lauren T. Hill, Terra Forero, Julian Restrepo Castro, Carlos Andrés C.R. Vigna, Matteo Ceriana, Piero Abu-El-rub, Noor Avillach, Paul Bellazzi, Riccardo Callaci, Thomas Gutiérrez-Sacristán, Alba Malovini, Alberto Mathew, Jomol P. Morris, Michele Murthy, Venkatesh Parimbelli, Enea Patel, Lav P. Sáez, Carlos Samayamuthu, Malarkodi Jebathilagam Thompson, Jeffrey A. Tibollo, Valentina Xia, Zongqi Kohane, Isaac S. Harvard Medical School Department of Biomedical Informatics 10 Shattuck Street BostonMA02115 United States School of Medicine and Public Health University of Wisconsin-Madison Office of Informatics and Information Technology 750 Highland Ave MadisonWI53705 United States University of Michigan Department of Computational Medicine & Bioinformatics Internal Medicine Human Genetics Environmental Health 100 Washtenaw Avenue Ann ArborMI48109 United States University of Kansas Medical Center Division of Medical Informatics Division of Pulmonary Critical Care and Sleep Medicine Department of Internal Medicine 3901 Rainbow Blvd Kansas CityKS66160 United States University of Antioquia Hospital Alma Máter de Antioquia Department of Internal Medicine Calle 64 N°51 D - 154 Medellín Colombia University of Pittsburgh Department of Biomedical Informatics 5607 Baum Blvd PittsburghPA15206 United States University of Pittsburgh Department of Neurology 3501 5th Avenue PittsburghPA15206 United States Boston Children's Hospital Computational Health Informatics Program 300 Longwood Avenue BostonMA02115 United States Boston Children's Hospital Department of Pediatrics 300 Longwood Avenue BostonMA02115 United States National University Health System Department of Surgery 1E Kent Ridge Rd Singapore119228 Singapore National University Health System Department of Diagnostic Imaging 1E Kent Ridge Rd Singapore119228 Singapore University of Michigan Department of Learning Health Sciences NCRC 100 2800 Plymouth Road Ann ArborMI48109 United States University of Kansas Medical Center Department of Surgery 3901 Rainbow Blvd Kansas CityKS66160 United States Istituti Clinici Scientifici Maugeri IRCCS Respiratory rehabilitation unit Via Maugeri 10 Pavia27100 Italy University of Kansas Medical Center 3901 Rainbow Blvd Kansas CityKS66160 United States University of Pavia Department of Electrical Computer and Biomedical Engineering via Ferrata 5 Pavia2710

Background: Physicians invest hours creating patient notes, which are rich in information but difficult for computers to analyze due to their unstructured format. GPT-4 reshaped our ability to process text, yet it is unknown how well this model can handle medical notes. This project aims to compare GPT-4’s ability to annotate medical notes against experienced physicians across three different languages at multiple institutions and countries. Methods: This study included eight sites from four countries - the United States, Colombia, Singapore, and Italy. Each site contributed seven de-identified notes (admission, progress, or consult) from hospitalized patients. GPT-4 assessed each note by answering 14 questions, including demographic information, clinical judgments, data quality, and patients’ eligibility for a hypothetical study enrollment. For validation, two physicians from each site independently evaluated GPT-4's responses. Findings: Overall, 56 medical notes, written in English, Italian, and Spanish, were analyzed. A total of 784 responses from GPT-4 were generated. Both physicians agreed with GPT-4’s response 79% of the time (622/784, 95%CI 76-82%). Only one of the two physicians agreed with GPT-4’s response 10% of the time (82/784, 95%CI 8-13%). Neither physician agreed with GPT-4’s response 10% of the time (80/784, 95%CI 8-13%). Both physicians agreed with GPT-4 more often in notes written in Spanish and Italian than in English, with agreement rates of 88% (86/98, 95%CI 79-93%), 84% (82/98, 95%CI 75-90%), and 77% (454/588, 95%CI 74-80%), respectively. Hallucinations were rare (10/784, 95%CI 0-2%). GPT-4 correctly selected patients for a hypothetical study enrollment based on three criteria 90% of the time (95%CI 81-98%). Interpretation: The findings indicate that GPT-4 annotations demonstrated a high agreement rate with physicians across all languages. We also demonstrate GPT-4's potential to assist in patient selection for studies. Funding: None. Declarati

关键词： medical computing

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TPFIANet: Three path feature progressive interactive attention learning network for medical image segmentation

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Knowledge-Based Systems 2025年 323卷

作者： Zhao, Yawu Wang, Shudong Ren, Yande Wang, Jiehuan Wang, Shaoqiang Qiao, Sibo Liu, Tiyao Pang, Shanchen Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software Qingdao Institute of Software College of Computer Science and Technology China University of Petroleum Qingdao Shandong China Department of Medical Imaging Center Affiliated Hospital of Qingdao University Qingdao Shandong China Department of Medical Imaging Affiliated Hospital of Jining Medical University Jining Shandong China School of Information and Control Engineering Qingdao University of Technology Qingdao Shandong China School of Software Tiangong University Tianjin China

In the field of medical image segmentation, medical image segmentation methods with high accuracy and generalization capabilities are crucial for driving personalized healthcare solutions and enhancing patient experience. To address the inherent challenges of difficulty in acquiring complex structural features and weak generalization ability in medical image segmentation, we propose a three-path spatial learning (TPSL) module, which takes advantage of convolutional neural networks (CNNs) to skillfully learn specific details at different scales to acquire better feature representations, and then, we propose a progressive feature cross-fusion (PFCF) module, which aims to dynamically learn feature information under different levels in the encoder, which enhances the feature representation. Finally, we propose the feature interactive attention fusion (FIAF) module, which mixes features from different scales and channels, adaptively learns feature weights and enhances the connection between channel and local spatial information. Based on the above modules, we design a three path feature progressive interactive attention learning network (TPFIANet), which captures image features at different levels and scales. We demonstrate the segmentation performance of TPFIANet on three public datasets and three self-organized datasets. Notably, our TPFIANet also demonstrates amiable segmentation performance on datasets of different modalities while maintaining a lighter architecture. © 2025

关键词： Image segmentation

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Existence of solutions of multi-order fractional differential equations

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Bouchelaghem, Faycal Boulares, Hamid Ardjouni, Abdelouaheb Jarad, Fahd Abdeljawad, Thabet Abdalla, Bahaaeldin Shah, Kamal High School of Management Sciences Annaba Annaba 23000 Algeria Laboratory of Analysis and Control of Differential Equations “ACED” Faculty MISM Department of Mathematics University of Guelma Guelma 24000 Algeria Department of Mathematics and Informatics Univ Souk Ahras P.O. Box 1553 Souk Ahras 41000 Algeria Department of Mathematics Cankaya University Etimesgut Ankara 06790 Türkiye Center for Applied Mathematics and Bioinformatics (CAMB) Gulf University for Science and Technology Hawally 32093 Kuwait Department of Mathematics and Sciences Prince Sultan University P.O. Box 66833 Riyadh 11586 Saudi Arabia Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai 602105 India Department of Mathematics and Applied Mathematics Sefako Makgatho Health Sciences University Garankuwa Medusa 0204 South Africa

Recently, the field of fractional calculus has garnered significant attention due to its wide range of applications across various disciplines in science and engineering. Numerous results have been derived using tools from numerical functional analysis and fixed point theory to address a variety of problems in this area. This study employs the Banach Fixed Point Theorem (BFPT) to establish the existence and uniqueness of solutions for Riemann–Liouville fractional differential equations (RLFDEs) involving multiple orders. Sufficient conditions for the existence of solutions to the problem under consideration have been provided. Furthermore, an illustrative example is presented to validate the theoretical findings. © 2025

关键词： Banach fixed point theorems Existence Multi-order Riemann–Liouville fractional derivatives Uniqueness

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Electronic structure and spatial inhomogeneity of iron-based superconductor FeS

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Chinese Physics B 2020年第4期29卷 110-115页

作者： Chengwei Wang Meixiao Wang Juan Jiang Haifeng Yang Lexian Yang Wujun Shi Xiaofang Lai Sung-Kwan Mo Alexei Barinov Binghai Yan Zhi Liu Fuqiang Huang Jinfeng Jia Zhongkai Liu Yulin Chen State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology(SIMIT)Chinese Academy of SciencesShanghai 200050China School of Physical Science and Technology ShanghaiTech UniversityCAS-Shanghai Science Research CenterShanghai 200031China University of Chinese Academic of Sciences Beijing 100049China Advanced Light Source Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA State Key Laboratory of Low Dimensional Quantum Physics Department of Physics and Collaborative Innovation Center for Quantum MatterTsinghua UniversityBeijing 100084China Beijing National Laboratory for Molecular Sciences and State Key Laboratory of Rare Earth Materials Chemistry and Applications College of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China Elettra-Sincrotrone Trieste ScPA TriesteBasovizza 34149Italy Max Planck Institute for Chemical Physics of Solids D-01187 DresdenGermany State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China Key Laboratory of Artificial Structures and Quantum Control(Ministry of Education) Department of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China Physics Department Oxford UniversityOxfordOX13PUUK

Iron-based superconductor family FeX(X=S,Se,Te)has been one of the research foci in physics and material science due to their record-breaking superconducting temperature(FeSe film)and rich physical ***,FeS,the least studied Fe X compound(due to the difficulty in synthesizing high quality macroscopic crystals)attracted much attention because of its puzzling superconducting pairing *** this work,combining scanning tunneling microscopy and angle resolved photoemission spectroscopy(ARPES)with sub-micron spatial resolution,we investigate the intrinsic electronic structures of superconducting FeS from individual single crystalline *** FeTe or FeSe,FeS remains identical tetragonal structure from room temperature down to 5 K,and the band structures observed can be well reproduced by our ab-initio ***,mixed with the 1×1 tetragonal metallic phase,we also observe the coexistence of √5×√5 reconstructed insulating phase in the crystal,which not only helps explain the unusual properties of FeS,but also demonstrates the importance of using spatially resolved experimental tools in the study of this compound.

关键词： angle-resolved photoemission with spatially resolution scanning tunneling microscopy iron-based superconductor electronic band structure

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Immunometabolic Pathways: Investigating Mediators of Major Depressive Disorder and Atherosclerotic Cardiovascular Disease Comorbidity

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Biological Psychiatry Global Open Science 2025年第5期5卷

作者： Angela Koloi Nabila P.R. Siregar Rick Quax Antonis I. Sakellarios Femke Lamers Arja Rydin Kevin Dobretz Costas Papaloukas Dimitrios I. Fotiadis Jos A. Bosch Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Ioannina Greece Department of Biological Applications and Technology University of Ioannina Ioannina Greece Department of Clinical Psychology University of Amsterdam Amsterdam the Netherlands Department of Medical Psychology Amsterdam University Medical Center Amsterdam the Netherlands Computational Science Laboratory Institute of Informatics University of Amsterdam Amsterdam the Netherlands Biomedical Engineering of the Department of Mechanical Engineering and Aeronautics University of Patras Patras Greece Department of Psychiatry Amsterdam University Medical Center VU Amsterdam Amsterdam the Netherlands Amsterdam Public Health Mental Health Program Amsterdam the Netherlands Cardiology Geneva University Hospitals Geneva Switzerland Department of Medicine University of Geneva Geneva Switzerland Biomedical Research Institute Foundation for Research and Technology - Hellas Ioannina Greece

Background Major depressive disorder (MDD) and cardiovascular diseases (CVDs) often co-occur whereby comorbidity results in poorer clinical outcomes, presumably due to shared immunometabolic pathways. Identifying shared biomarkers for MDD-CVD comorbidity may provide targets for prevention or treatment. Methods Using data from the NESDA (Netherlands Study of Depression and Anxiety) ( n = 2256, 66.3% female, mean age 41.86 ± 13.08 years at baseline), validated with the UK Biobank (UKB) data ( n = 35,668, 56.14% female, mean age 63.95 ± 7.74 years), this study aimed to identify 1) biomarkers, closely associated with current MDD, and 2) longitudinal pathways linking MDD and atherosclerotic CVD. Plasma metabolites (nuclear magnetic resonance) and inflammatory markers were used as exposures within a machine learning framework. Influential biomarkers were integrated into a temporal network analysis linking MDD to subsequent CVDs, exploring longitudinal pathways through causal discovery, validated by sensitivity analysis and centrality assessment. External validation included mediation and regression analysis adjusting for covariates. Results Network analysis identified stable direct paths from MDD to CVDs via tumor necrosis factor α (TNF-α), tyrosine, and fatty acids and indirect paths via acetate, high-density lipoprotein (HDL) diameter, interleukin 6, AGP, high-sensitivity C-reactive protein, and low-density lipoprotein triglycerides. Among these, acetate, tyrosine, AGP (α 1 -acid glycoprotein), and HDL diameter potentially mediated the MDD-CVD connection, given that these were identified as key nodes within the network. UKB validation confirmed HDL diameter (β = 0.004) and AGP (β = 0.003) as significant depression-CVD mediators (both p < .001), after adjusting for age, sex, deprivation index, alcohol consumption, smoking status, physical activity, and body mass index. Conclusions These analyses identified biomarkers shared in MDD and CVDs and may drive comorbid patholog

关键词： Biomarkers CVD Machine learning MDD Mediators

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Renal Clearing Carbon Dots-Based Near-Infrared Fluorescent Super-Small Nanoprobe for Renal Imaging

SSRN

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SSRN 2022年

作者： Gao, Pengli Hui, Hui Guo, Chanjuan Liu, Yu Su, Ya Huang, Xiazi Shang, Wenting Jiang, Jingying Tian, Jie Guo, Kunxiong CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imaging The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Biological Science and Medicine Engineering School of Engineering Medicine Beihang University No. 37 Xueyuan Road Beijing100191 China Key Laboratory of Big Data-Based Precision Medicine Beihang University Ministry of Industry and Information Technology of the People’s Republic of China No. 37 Xueyuan Road Beijing100191 China School of Engineering Medicine Beihang University No. 37 Xueyuan Road Beijing100191 China Department of Hepatobiliary Surgery Zhujiang Hospital Southern Medical University Guangzhou China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine China

Real-time renal imaging is indispensable for monitoring kidney-related disease processes and evaluating the nephrotoxicity of nanoprobes. Owing to their small size, tunable photoluminescence properties, and low biotoxicity, carbon dots (CDs) are widely employed as nanoprobes for imaging-guided disease diagnosis. However, the preparation of near-infrared CDs is a stupendous challenging. Here, CDs with near-infrared fluorescence (NIR-CDs ) were prepared by one-pot pyrolysis and were comprehensively evaluated for real-time renal imaging. The NIR-CDs possessed super-small size (1.8 ± 0.2 nm) and high quantum yield (14.3% in aqueous solution) at 696 nm. NIR-CDs exhibited high-efficiency renal clearance at 24 h post-treatment (97.47-99.27% ID) via glomerular filtration. The irreversible clearance of NIR-CDs enables effective real-time monitoring of kidney function in the normal and acute kidney injury (AKI) mouse models. Consequently, NIR-CDs can be utilized for imaging analyses of impaired kidney function, pioneering a serviceable guideline for neoapplications of NIR-CDs. © 2022, The Authors. All rights reserved.

关键词： Nanoprobes

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