Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging

Miaomiao WANG; Lu GAN; Yiru FAN; Chenxi DUAN; Ying ZHU; Shihua LUO; Yanhong SUN

doi:10.1631/jzus.B2500786

Your Location：

Home >

Browse articles >

Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging

Scan QR Code

Alert me when the article has been cited

Submit

Review | Updated：2026-07-29

Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging
Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging
血脑屏障通透性评估技术进展：从仿生模型到多模态成像
Journal of Zhejiang University-SCIENCE B Vol. 27, Issue 7, Pages: 715-735(2026)
Affiliations：

1.Institute of Materiobiology, College of Sciences, Shanghai University, Shanghai 200444, China
2.Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.Department of Traumatology, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China
Funds：
DOI：10.1631/jzus.B2500786
CLC：
CSTR：
Received：01 December 2025，

Revised：2026-03-12，

Online First：29 July 2026，

Published：15 July 2026
Accepted：

王苗苗,甘露,凡怡茹等.血脑屏障通透性评估技术进展：从仿生模型到多模态成像[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2026,27(07):715-735.

Miaomiao WANG, Lu GAN, Yiru FAN, et al. Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging[J]. Journal of Zhejiang University-SCIENCE B, 2026, 27(7): 715-735.
王苗苗,甘露,凡怡茹等.血脑屏障通透性评估技术进展：从仿生模型到多模态成像[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2026,27(07):715-735. DOI： 10.1631/jzus.B2500786.

Miaomiao WANG, Lu GAN, Yiru FAN, et al. Blood‒brain barrier permeability assessment: from biomimetic models to multimodal imaging[J]. Journal of Zhejiang University-SCIENCE B, 2026, 27(7): 715-735. DOI： 10.1631/jzus.B2500786.

摘要

血脑屏障（BBB）是维持中枢神经系统内环境稳态的核心结构，其通透性调控失衡是脑卒中、神经退行性疾病和脑肿瘤等多种神经系统疾病的关键病理环节，也是中枢神经系统药物递送的主要瓶颈。因此，发展精准的BBB通透性检测技术，对于揭示神经疾病机制、突破药物研发瓶颈及推动精准诊疗至关重要。本文系统梳理了BBB通透性检测技术的最新进展：体外模型方面，概述了从传统Transwell体系到整合流体剪切力的微流控芯片及高度仿生类器官模型的演进，重点评价其对神经血管单元微环境模拟能力的提升；活体成像技术方面，深入分析了动态对比增强磁共振成像、正电子发射断层扫描、近红外二区荧光成像及双光子显微镜等技术的原理与应用，阐述了其在宏观定量、分子靶向及微观动态观测等方面的互补优势。多模态技术融合与精准量化评估是当前主要发展趋势。未来研究将聚焦于人工智能驱动的个性化BBB通透性评估、新型智能化探针开发以及BBB功能的实时动态监测，从而为神经系统疾病研究提供更强大的方法学工具。

Abstract

The blood‒brain barrier (BBB) is a vital physiological structure that maintains the microenvironmental homeostasis in the central nervous system (CNS). Imbalances in its permeability play a key role in various neurological disorders

including stroke

neurodegenerative diseases

and brain tumors. The development of precise techniques for assessing BBB permeability is therefore paramount for elucidating the mechanisms of neurological diseases

overcoming drug development challenges

and achieving precise diagnosis and treatment of CNS disorders. This review systematically summarizes the latest advances in the assessment of BBB permeability. Regarding in vitro models

platforms have evolved from the traditional transwell system to microfluidic chips incorporating fluid shear forces and subsequently to highly biomimetic brain organoids

with continuous improvements in the ability to simulate the neurovascular unit (NVU) microenvironment. For in vivo assessment

we detail the principles and applications of imaging techniques

including dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

positron emission tomography (PET)

near-infrared II (NIR-II) fluorescence imaging (FI)

and two-photon microscopy (TPM)

highlighting their complementary strengths in macroscopic quantification

molecular targeting

and microscopic dynamic observation. The integration of multi-modal technologies and precise quantitative assessment is a prominent trend. Future investigations will focus on artificial intelligence (AI)-driven personalized permeability assessment

the development of novel intelligent probes

and the dynamic real-time monitoring of the BBB

thereby providing powerful methodological support for neurological disease research.

关键词

Keywords

references

Ahlawat J , Barroso GG , Asil SM , et al. , 2020 . Nanocarriers as potential drug delivery candidates for overcoming the blood‒brain barrier: challenges and possibilities . ACS Omega , 5 ( 22 ): 12583 - 12595 . https://doi.org/10.1021/acsomega.0c01592 https://doi.org/10.1021/acsomega.0c01592

Ambudkar SV , Dey S , Hrycyna CA , et al. , 1999 . Biochemical, cellular, and pharmacological aspects of the multidrug transporter . Annu Rev Pharmacol Toxicol , 39 : 361 - 398 . https://doi.org/10.1146/annurev.pharmtox.39.1.361 https://doi.org/10.1146/annurev.pharmtox.39.1.361

Anderson JM , van Itallie CM , 2009 . Physiology and function of the tight junction . Cold Spring Harb Perspect Biol , 1 : a002584 . https://doi.org/10.1101/cshperspect.a002584 https://doi.org/10.1101/cshperspect.a002584

Appelt-Menzel A , Cubukova A , Günther K , et al. , 2017 . Establishment of a human blood‒brain barrier co-culture model mimicking the neurovascular unit using induced pluri- and multipotent stem cells . Stem Cell Rep , 8 ( 4 ): 894 - 906 . https://doi.org/10.1016/j.stemcr.2017.02.021 https://doi.org/10.1016/j.stemcr.2017.02.021

Badiola-Mateos M , di Giuseppe D , Paoli R , et al. , 2021 . A novel multi-frequency trans-endothelial electrical resistance (MTEER) sensor array to monitor blood‒brain barrier integrity . Sens Actuators B Chem , 334 : 129599 . https://doi.org/10.1016/j.snb.2021.129599 https://doi.org/10.1016/j.snb.2021.129599

Bagchi S , Chhibber T , Lahooti B , et al. , 2019 . In-vitro blood‒brain barrier models for drug screening and permeation studies: an overview . Drug Des Devel Ther , 13 : 3591 - 3605 . https://doi.org/10.2147/dddt.s218708 https://doi.org/10.2147/dddt.s218708

Balzer V , Poc P , Puris E , et al. , 2022 . Re-evaluation of the hCMEC/D3 based in vitro BBB model for ABC transporter studies . Eur J Pharm Biopharm , 173 : 12 - 21 . https://doi.org/10.1016/j.ejpb.2022.02.017 https://doi.org/10.1016/j.ejpb.2022.02.017

Banerjee J , Shi YJ , Azevedo HS , 2016 . In vitro blood‒brain barrier models for drug research: state-of-the-art and new perspectives on reconstituting these models on artificial basement membrane platforms . Drug Discov Today , 21 ( 9 ): 1367 - 1386 . https://doi.org/10.1016/j.drudis.2016.05.020 https://doi.org/10.1016/j.drudis.2016.05.020

Banks WA , 2016 . From blood‒brain barrier to blood‒brain interface: new opportunities for CNS drug delivery . Nat Rev Drug Discov , 15 : 275 - 292 . https://doi.org/10.1038/nrd.2015.21 https://doi.org/10.1038/nrd.2015.21

Bayir E , Celtikoglu MM , Sendemir A , 2019 . The use of bacterial cellulose as a basem ent membrane improves the plausibility of the static in vitro blood‒brain barrier model . Int J Biol Macromol , 126 : 1002 - 1013 . https://doi.org/10.1016/j.ijbiomac.2018.12.257 https://doi.org/10.1016/j.ijbiomac.2018.12.257

Bell RD , Winkler EA , Sagare AP , et al. , 2010 . Pericytes control key neurovascular functions and neuronal phenotype in the adult brain and during brain aging . Neuron , 68 ( 3 ): 409 - 427 . https://doi.org/10.1016/j.neuron.2010.09.043 https://doi.org/10.1016/j.neuron.2010.09.043

Benson K , Cramer S , Galla HJ , 2013 . Impedance-based cell monitoring: barrier properties and beyond . Fluids Barriers CNS , 10 : 5 . https://doi.org/10.1186/2045-8118-10-5 https://doi.org/10.1186/2045-8118-10-5

Bergmann S , Lawler SE , Qu Y , et al. , 2018 . Blood‒brain-barrier organoids for investigating the permeability of CNS therapeutics . Nat Protoc , 13 ( 12 ): 2827 - 2843 . https:/doi.org/10.1038/s41596-018-0066-x https://doi.org/10.1038/s41596-018-0066-x

Bhattacharya A , Kaushik DK , Lozinski BM , et al. , 2020 . Beyond barrier functions: roles of pericytes in homeostasis and regulation of neuroinflammation . J Neurosci Res , 98 ( 12 ): 2390 - 2405 . https://doi.org/10.1002/jnr.24715 https://doi.org/10.1002/jnr.24715

Cao J , Zhu BL , Zheng KF , et al. , 2020 . Recent progress in NIR-II contrast agent for biological imaging . Front Bioeng Biotechnol , 7 : 487 . https://doi.org/10.3389/fbioe.2019.00487 https://doi.org/10.3389/fbioe.2019.00487

Cao PY , He Y , Cui MY , et al. , 2024 . Group graph: a molecular graph representation with enhanced performance, efficiency and interpretability . J Cheminform , 16 : 133 . https://doi.org/10.1186/s13321-024-00933-x https://doi.org/10.1186/s13321-024-00933-x

Ceccarelli MC , Lefevre MC , Marino A , et al. , 2024 . Real-time monitoring of a 3D blood‒brain barrier model maturation and integrity with a sensorized microfluidic device . Lab Chip , 24 ( 22 ): 5085 - 5100 . https://doi.org/10.1039/d4lc00633j https://doi.org/10.1039/d4lc00633j

Cecchelli R , Berezowski V , Lundquist S , et al. , 2007 . Modelling of the blood‒brain barrier in drug discovery and development . Nat Rev Drug Discov , 6 : 650 - 661 . https://doi.org/10.1038/nrd2368 https://doi.org/10.1038/nrd2368

Chen HJ , Tong X , Lang LX , et al. , 2017 . Quantification of tumor vascular permeability and blood volume by positron emission tomography . Theranostics , 7 ( 9 ): 2363 - 2376 . https://doi.org/10.7150/thno.19898 https://doi.org/10.7150/thno.19898

Chen HY , Mirg S , Gaddale P , et al. , 2024 . Multiparametric brain hemodynamics imaging using a combined ultrafast ultrasound and photoacoustic system . Adv Sci , 11 ( 31 ): 2401467 . https://doi.org/10.1002/advs.202401467 https://doi.org/10.1002/advs.202401467

Chen XY , Xu J , Guo SY , et al. , 2024 . Blood‒brain barrier permeability by CT perfusion predicts parenchymal hematoma after recanalization with thrombectomy . J Neuroimaging , 34 ( 2 ): 241 - 248 . https://doi.org/10.1111/jon.13172 https://doi.org/10.1111/jon.13172

Chung B , Kim J , Nam J , et al. , 2020 . Evaluation of cell-penetrating peptides using microfluidic in vitro 3D brain endothelial barrier . Macromol Biosci , 20 ( 6 ): 1900425 . https://doi.org/10.1002/mabi.201900425 https://doi.org/10.1002/mabi.201900425

Chung KJ , Abdelhafez YG , Spencer BA , et al. , 2025 . Quantitative PET imaging and modeling of molecular blood‒brain barrier permeability . Nat Commun , 16 : 3076 . https://doi.org/10.1038/s41467-025-58356-7 https://doi.org/10.1038/s41467-025-58356-7

Clark DE , 2003 . In silico prediction of blood‒brain barrier permeation . Drug Discov Today , 8 ( 20 ): 927 - 933 . https://doi.org/10.1016/S1359-6446(03)02827-7 https://doi.org/10.1016/S1359-6446(03)02827-7

Cornford EM , Hyman S , 1999 . Blood‒brain barrier permeability to small and large molecules . Adv Drug Deliv Rev , 36 ( 2-3 ): 145 - 163 . https://doi.org/10.1016/S0169-409X(98)00082-9 https://doi.org/10.1016/S0169-409X(98)00082-9

Cucullo L , Couraud PO , Weksler B , et al. , 2008 . Immortalized human brain endothelial cells and flow-based vascular modeling: a marriage of convenience for rational neurovascular studies . J Cereb Blood Flow Metab , 28 ( 2 ): 312 - 328 . https://doi.org/10.1038/sj.jcbfm.9600525 https://doi.org/10.1038/sj.jcbfm.9600525

Cucullo L , Marchi N , Hossain M , et al. , 2011 . A dynamic in vitro BBB model for the study of immune cell trafficking into the central nervous system . J Cereb Blood Flow Metab , 31 ( 2 ): 767 - 777 . https://doi.org/10.1038/jcbfm.2010.162 https://doi.org/10.1038/jcbfm.2010.162

Dai JF , Wei WJ , Yan CX , et al. , 2025 . Multiplex imaging of amyloid-β plaques dynamics in living brains with quinoline-malononitrile-based probes . Nat Biomed Eng , 9 : 1632 - 1644 . https://doi.org/10.1038/s41551-025-01392-x https://doi.org/10.1038/s41551-025-01392-x

Daniels BP , Cruz-Orengo L , Pasieka TJ , et al. , 2013 . Immortalized human cerebral microvascular endothelial cells maintain the properties of primary cells in an in vitro model of immune migration across the blood brain barrier . J Neurosci Methods , 212 ( 1 ): 173 - 179 . https://doi.org/10.1016/j.jneumeth.2012.10.001 https://doi.org/10.1016/j.jneumeth.2012.10.001

Dao L , You Z , Lu L , et al. , 2024 . Modeling blood‒brain barrier formation and cerebral cavernous malformations in human PSC-derived organoids . Cell Stem Cell , 31 ( 6 ): 818 - 833.e11 . https://doi.org/10.1016/j.stem.2024.04.019 https://doi.org/10.1016/j.stem.2024.04.019

de Vivo DC , Trifiletti RR , Jacobson RI , et al. , 1991 . Defective glucose transport across the blood‒brain barrier as a cause of persistent hypoglycorrhachia, seizures, and developmental delay . N Engl J Med , 325 ( 10 ): 703 - 709 . https://doi.org/10.1056/nejm199109053251006 https://doi.org/10.1056/nejm199109053251006

Deli MA , Ábrahám CS , Kataoka Y , et al. , 2005 . Permeability studies on in vitro blood‒brain barrier models: physiology, pathology, and pharmacology . Cell Mol Neurobiol , 25 : 59 - 127 . https://doi.org/10.1007/s10571-004-1377-8 https://doi.org/10.1007/s10571-004-1377-8

Denk W , Strickler JH , Webb WW , 1990 . Two-photon laser scanning fluorescence microscopy . Science , 248 : 73 - 76 . https://doi.org/10.1126/science.2321027 https://doi.org/10.1126/science.2321027

Dey V , Ning X , 2024 . Enhancing molecular property prediction with auxiliary learning and task-specific adaptation . J Cheminform , 16 : 85 . https://doi.org/10.1186/s13321-024-00880-7 https://doi.org/10.1186/s13321-024-00880-7

Dohgu S , Takata F , Yamauchi A , et al. , 2005 . Brain pericytes contribute to the induction and up-regulation of blood‒brain barrier functions through transforming growth factor-β production . Brain Res , 1038 ( 2 ): 208 - 215 . https://doi.org/10.1016/j.brainres.2005.01.027 https://doi.org/10.1016/j.brainres.2005.01.027

Dong XW , 2018 . Current strategies for brain drug delivery . Theranostics , 8 ( 6 ): 1481 - 1493 . https://doi.org/10.7150/thno.21254 https://doi.org/10.7150/thno.21254

Douville NJ , Tung YC , Li R , et al. , 2010 . Fabrication of two-layered channel system with embedded electrodes to measure resistance across epithelial and endothelial barriers . Anal Chem , 82 ( 6 ): 2505 - 2511 . https://doi.org/10.1021/ac9029345 https://doi.org/10.1021/ac9029345

Fernández‐Seara MA , Wang Z , Wang JJ , et al. , 2005 . Continuous arterial spin labeling perfusion measurements using single shot 3D GRASE at 3 T . Magn Reson Med , 54 ( 5 ): 1241 - 1247 . https://doi.org/10.1002/mrm.20674 https://doi.org/10.1002/mrm.20674

Franke H , Galla HJ , Beuckmann CT , 1999 . An improved low-permeability in vitro-model of the blood‒brain barrier: transport studies on retinoids, sucrose, haloperidol, caffeine and mannitol . Brain Res , 818 ( 1 ): 65 - 71 . https://doi.org/10.1016/S0006-8993(98)01282-7 https://doi.org/10.1016/S0006-8993(98)01282-7

Grant N , Machado Reyes D , Yang ZF , et al. , 2025 . Blood brain barrier permeability prediction with artificial intelligence and machine learning: a meta-review and future directions . Discov Artif Intell , 5 : 254 . https://doi.org/10.1007/s44163-025-00494-4 https://doi.org/10.1007/s44163-025-00494-4

Grkovski R , Acu L , Ahmadli U , et al. , 2023a . A novel dual-energy CT method for detection and differentiation of intracerebral hemorrhage from contrast extravasation in stroke patients after endovascular thrombectomy: feasibility and first results . Clin Neuroradiol , 33 : 171 - 177 . https://doi.org/10.1007/s00062-022-01198-3 https://doi.org/10.1007/s00062-022-01198-3

Grkovski R , Acu L , Ahmadli U , et al. , 2023b . Dual-energy computed tomography in stroke imaging: value of a new image acquisition technique for ischemia detection after mechanical thrombectomy . Clin Neuroradiol , 33 : 747 - 754 . https://doi.org/10.1007/s00062-023-01270-6 https://doi.org/10.1007/s00062-023-01270-6

Hajal C , Offeddu GS , Shin Y , et al. , 2022 . Engineered human blood‒brain barrier microfluidic model for vascular permeability analyses . Nat Protoc , 17 : 95 - 128 . https://doi.org/10.1038/s41596-021-00635-w https://doi.org/10.1038/s41596-021-00635-w

Harilal S , Jose J , Parambi DGT , et al. , 2020 . Revisiting the blood‒brain barrier: a hard nut to crack in the transportation of drug molecules . Brain Res Bull , 160 : 121 - 140 . https://doi.org/10.1016/j.brainresbull.2020.03.018 https://doi.org/10.1016/j.brainresbull.2020.03.018

He QG , Liu J , Liang J , et al. , 2018 . Towards improvements for penetrating the blood-brain barrier—recent progress from a material and pharmaceutical perspective . Cells , 7 ( 4 ): 24 . https://doi.org/10.3390/cells7040024 https://doi.org/10.3390/cells7040024

Heye AK , Culling RD , Hernández MDCV , et al. , 2014 . Assessment of blood‒brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review . Neuroimage Clin , 6 : 262 - 274 . https://doi.org/10.1016/j.nicl.2014.09.002 https://doi.org/10.1016/j.nicl.2014.09.002

Hong GS , Lee JC , Robinson JT , et al. , 2012 . Multifunctional in vivo vascular imaging using near-infrared II fluorescence . Nat Med , 18 : 1841 - 1846 . https://doi.org/10.1038/nm.2995 https://doi.org/10.1038/nm.2995

Hong GS , Antaris AL , Dai HJ , 2017 . Near-infrared fluorophores for biomedical imaging . Nat Biomed Eng , 1 : 0010 . https://doi.org/10.1038/s41551-016-0010 https://doi.org/10.1038/s41551-016-0010

Hui J , Li R , Phillips EH , et al. , 2016 . Bond-selective photoacoustic imaging by converting molecular vibration into acoustic waves . Photoacoustics , 4 : 11 - 21 . https://doi.org/10.1016/j.pacs.2016.01.002 https://doi.org/10.1016/j.pacs.2016.01.002

Hurst RD , Fritz IB , 1996 . Properties of an immortalised vascular endothelial/glioma cell co-culture model of the blood‒brain barrier . J Cell Physiol , 167 : 81 - 88 . https://doi.org/10.1002/(SICI)1097-4652(199604)167:1<81::AID-JCP9>3.0.CO;2-8 https://doi.org/10.1002/(SICI)1097-4652(199604)167:1<81::AID-JCP9>3.0.CO;2-8

Iliff JJ , Wang MH , Liao YH , et al. , 2012 . A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β . Sci Transl Med , 4:147ra111. https://doi.org/10.1126/scitranslmed.3003748 https://doi.org/10.1126/scitranslmed.3003748

Ito R , Umehara K , Suzuki S , et al. , 2019 . A human immortalized cell-based blood‒brain barrier triculture model: development and characterization as a promising tool for drug‒brain permeability studies . Mol Pharm , 16 ( 11 ): 4461 - 4471 . https://doi.org/10.1021/acs.molpharmaceut.9b00519 https://doi.org/10.1021/acs.molpharmaceut.9b00519

Jackson I , Luo A , Webb E , et al. , 2021 . A new in silico approach to revolutionize CNS PET tracer design and enhance translational success . Nucl Med Biol , 96 - 97 : S24 - S25 . https://doi.org/10.1016/S0969-8051(21)00304-8 https://doi.org/10.1016/S0969-8051(21)00304-8

Janigro D , Leaman SM , Stanness KA , 1999 . Dynamic in vitro modeling of the blood‒brain barrier: a novel tool for studies of drug delivery to the brain . Pharm Sci Technol Today , 2 : 7 - 12 . https://doi.org/10.1016/s1461-5347(98)00110-2 https://doi.org/10.1016/s1461-5347(98)00110-2

Jiang DJ , Wu ZX , Hsieh CY , et al. , 2021 . Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models . J Cheminform , 13 : 12 . https://doi.org/10.1186/s13321-020-00479-8 https://doi.org/10.1186/s13321-020-00479-8

Jiang LL , Li S , Zheng JS , et al. , 2019 . Recent progress in microfluidic models of the blood‒brain barrier . Micromachines , 10 ( 6 ): 375 . https://doi.org/10.3390/mi10060375 https://doi.org/10.3390/mi10060375

Johnson TRC , Krauß B , Sedlmair M , et al. , 2007 . Material differentiation by dual energy CT: initial experience . Eur Radiol , 17 ( 6 ): 1510 - 1517 . https://doi.org/10.1007/s00330-006-0517-6 https://doi.org/10.1007/s00330-006-0517-6

Juliano RL , Ling V , 1976 . A surface glycoprotein modulating drug permeability in Chinese hamster ovary cell mutants . Biochim Biophys Acta (BBA)-Biomembr , 455 : 152 - 162 . https://doi.org/10.1016/0005-2736(76)90160-7 https://doi.org/10.1016/0005-2736(76)90160-7

Kadry H , Noorani B , Cucullo L , 2020 . A blood‒brain barrier overview on structure, function, impairment, and biomarkers of integrity . Fluids Barriers CNS , 17 : 69 . https://doi.org/10.1186/s12987-020-00230-3 https://doi.org/10.1186/s12987-020-00230-3

Kisler K , Nelson AR , Rege SV , et al. , 2017 . Pericyte degeneration leads to neurovascular uncoupling and limits oxygen supply to brain . Nat Neurosci , 20 : 406 - 416 . https://doi.org/10.1038/nn.4489 https://doi.org/10.1038/nn.4489

Krol S , Macrez R , Docagne F , et al. , 2013 . Therapeutic benefits from nanoparticles: the potential significance of nanoscience in diseases with compromise to the blood brain barrier . Chem Rev , 113 ( 3 ): 1877 - 1903 . https://doi.org/10.1021/cr200472g https://doi.org/10.1021/cr200472g

Lee S , Kang BM , Kim JH , et al. , 2018 . Real-time in vivo two-photon imaging study reveals decreased cerebro-vascular volume and increased blood‒brain barrier permeability in chronically stressed mice . Sci Rep , 8 : 13064 . https://doi.org/10.1038/s41598-018-30875-y https://doi.org/10.1038/s41598-018-30875-y

Li J , Wang TT , Zhang X , et al. , 2025 . Chalcogenapyrylium-engineered D-π-A probe for enhanced optoacoustic imaging of amyloid-β plaques . Sens Actuators B Chem , 442 : 138086 . https://doi.org/10.1016/j.snb.2025.138086 https://doi.org/10.1016/j.snb.2025.138086

Li WJ , Zha XC , Zhang XY , et al. , 2025 . Enhanced positron emission tomography imaging of β-amyloid through focused ultrasound-mediated gallium-68 radiotracer delivery across the blood‒brain barrier . ACS Chem Neurosci , 16 ( 15 ): 3070 - 3081 . https://doi.org/10.1021/acschemneuro.5c00476 https://doi.org/10.1021/acschemneuro.5c00476

Li XH , Fourches D , 2020 . Inductive transfer learning for molecular activity prediction: Next-Gen QSAR Models with MolPMoFiT . J Cheminform , 12 : 27 . https://doi.org/10.1186/s13321-020-00430-x https://doi.org/10.1186/s13321-020-00430-x

Lin L , Wang LV , 2022 . The emerging role of photoacoustic imaging in clinical oncology . Nat Rev Clin Oncol , 19 : 365 - 384 . https://doi.org/10.1038/s41571-022-00615-3 https://doi.org/10.1038/s41571-022-00615-3

Lin ZX , Li Y , Su P , et al. , 2018 . Non-contrast MR imaging of blood‒brain barrier permeability to water . Magn Reson Med , 80 ( 4 ): 1507 - 1520 . https://doi.org/10.1002/mrm.271411 https://doi.org/10.1002/mrm.271411

Liu JJ , Wang T , Dong J , et al. , 2025 . The blood-brain barriers: novel nanocarriers for central nervous system diseases . J Nanobiotechnol , 23 : 146 . https://doi.org/10.1186/s12951-025-03247-8 https://doi.org/10.1186/s12951-025-03247-8

Liu LL , Zhang L , Feng HW , et al. , 2021 . Prediction of the blood‒brain barrier (BBB) permeability of chemicals based on machine-learning and ensemble methods . Chem Res Toxicol , 34 ( 6 ): 1456 - 1467 . https://doi.org/10.1021/acs.chemrestox.0c00343 https://doi.org/10.1021/acs.chemrestox.0c00343

Liu PY , Uh J , Lu HZ , 2011 . Determination of spin compartment in arterial spin labeling MRI . Magn Reson Med , 65 ( 1 ): 120 - 127 . https://doi.org/10.1002/mrm.22601 https://doi.org/10.1002/mrm.22601

Liu XG , Duan YK , Liu B , 2021 . Nanoparticles as contrast agents for photoacoustic brain imaging . Aggregate , 2 : 4 - 19 . https://doi.org/10.1002/agt2.26 https://doi.org/10.1002/agt2.26

Logan S , Arzua T , Canfield SG , et al. , 2019 . Studying human neurological disorders using induced pluripotent stem cells: from 2D monolayer to 3D organoid and blood brain barrier models . Compr Physiol , 9 ( 2 ): 565 - 611 . https://doi.org/10.1002/j.2040-4603.2019.tb00076.x https://doi.org/10.1002/j.2040-4603.2019.tb00076.x

Lu C , Meng C , Li YY , et al. , 2024 . A probe for NIR-II imaging and multimodal analysis of early Alzheimer’s disease by targeting CTGF . Nat Commun , 15 : 5000 . https://doi.org/10.1038/s41467-024-49409-4 https://doi.org/10.1038/s41467-024-49409-4

Luissint AC , Artus C , Glacial F , et al. , 2012 . Tight junctions at the blood brain barrier: physiological architecture and disease-associated dysregulation . Fluids Barriers CNS , 9 : 23 . https://doi.org/10.1186/2045-8118-9-23 https://doi.org/10.1186/2045-8118-9-23

Malik M , Steele SA , Mitra D , et al. , 2025 . Trans-epithelial/endothelial electrical resistance (TEER): current state of integrated TEER measurements in organ-on-a-chip devices . Curr Opin Biomed Eng , 34 : 100588 . https://doi.org/10.1016/j.cobme.2025.100588 https://doi.org/10.1016/j.cobme.2025.100588

Malinova TS , Huveneers S , 2018 . Sensing of cytoskeletal forces by asymmetric adherens junctions . Trends Cell Biol , 28 ( 4 ): 328 - 341 . https://doi.org/10.1016/j.tcb.2017.11.002 https://doi.org/10.1016/j.tcb.2017.11.002

Mantecón-Oria M , Diban N , Berciano MT , et al. , 2020 . Hollow fiber membranes of PCL and PCL/graphene as scaffolds with potential to develop in vitro blood‒brain barrier models . Membranes , 10 ( 8 ): 161 . https://doi.org/10.3390/membranes10080161 https://doi.org/10.3390/membranes10080161

Mantecón-Oria M , Tapia O , Lafarga M , et al. , 2022a . Influence of the properties of different graphene-based nanomaterials dispersed in polycaprolactone membranes on astrocytic differentiation . Sci Rep , 12 : 13408 . https://doi.org/10.1038/s41598-022-17697-9 https://doi.org/10.1038/s41598-022-17697-9

Mantecón-Oria M , Rivero MJ , Diban N , et al. , 2022b . On the quest of reliable 3D dynamic in vitro blood‒brain barrier models using polymer hollow fiber membranes: pitfalls, progress, and future perspectives . Front Bioeng Biotechnol , 10 : 1056162 . https://doi.org/10.3389/fbioe.2022.1056162 https://doi.org/10.3389/fbioe.2022.1056162

Mantecón-Oria M , Rivero MJ , Löscher W , et al. , 2025 . Breaking optical barriers: transparent polymeric hollow fibers for biomedical applications . View , 6 ( 6 ): 20250076 . https://doi.org/10.1002/VIW.20250076 https://doi.org/10.1002/VIW.20250076

Mármol I , Abizanda-Campo S , Ayuso JM , et al. , 2023 . Towards novel biomimetic in vitro models of the blood‒brain barrier for drug permeability evaluation . Bioengineering , 10 ( 5 ): 572 . https://doi.org/10.3390/bioengineering10050572 https://doi.org/10.3390/bioengineering10050572

Miles KA , Griffiths MR , 2003 . Perfusion CT: a worthwhile enhancement? Br J Radiol , 76 : 220 - 231 . https://doi.org/10.1259/bjr/13564625 https://doi.org/10.1259/bjr/13564625

Mouchtouris N , Ailes I , Gooch R , et al. , 2024 . Quantifying blood‒brain barrier permeability in patients with ischemic stroke using non-contrast MRI . Magn Reson Imaging , 109 : 165 - 172 . https://doi.org/10.1016/j.mri.2024.03.027 https://doi.org/10.1016/j.mri.2024.03.027

Muruganandam A , Herx LM , Monette R , et al. , 1997 . Development of immortalized human cerebromicrovascular endothelial cell line as an in vitro model of the human blood‒brain barrier . FASEB J , 11 ( 13 ): 1187 - 1197 . https://doi.org/10.1096/fasebj.11.13.9367354 https://doi.org/10.1096/fasebj.11.13.9367354

Naik P , Cucullo L , 2012 . In vitro blood‒brain barrier models: current and perspective technologies . J Pharm Sci , 101 ( 4 ): 1337 - 1354 . https://doi.org/10.1002/jps.23022 https://doi.org/10.1002/jps.23022

Nakagawa S , Deli MA , Kawaguchi H , et al. , 2009 . A new blood‒brain barrier model using primary rat brain endothelial cells, pericytes and astrocytes . Neurochem Int , 54 ( 3-4 ): 253 - 263 . https://doi.org/10.1016/j.neuint.2008.12.002 https://doi.org/10.1016/j.neuint.2008.12.002

Nation DA , Sweeney MD , Montagne A , et al. , 2019 . Blood‒brain barrier breakdown is an early biomarker of human cognitive dysfunction . Nat Med , 25 : 270 - 276 . https://doi.org/10.1038/s41591-018-0297-y https://doi.org/10.1038/s41591-018-0297-y

Nazari H , Shrestha J , Naei VY , et al. , 2023 . Advances in TEER measurements of biological barriers in microphysiological systems . Biosens Bioelectron , 234 : 115355 . https://doi.org/10.1016/j.bios.2023.115355 https://doi.org/10.1016/j.bios.2023.115355

Neuhaus W , Lauer R , Oelzant S , et al. , 2006 . A novel flow based hollow-fiber blood‒brain barrier in vitro model with immortalised cell line PBMEC/C1-2 . J Biotechnol , 125 ( 1 ): 127 - 141 . https://doi.org/10.1016/j.jbiotec.2006.02.019 https://doi.org/10.1016/j.jbiotec.2006.02.019

Nogueira DES , Cabral JMS , Rodrigues CAV , 2021 . Single-use bioreactors for human pluripotent and adult stem cells: towards regenerative medicine applications . Bioengineering , 8 ( 5 ): 68 . https://doi.org/10.3390/bioengineering8050068 https://doi.org/10.3390/bioengineering8050068

Nzou G , Wicks RT , Wicks EE , et al. , 2018 . Human cortex spheroid with a functional blood brain barrier for high-throughput neurotoxicity screening and disease modeling . Sci Rep , 8 : 7413 . https://doi.org/10.1038/s41598-018-25603-5 https://doi.org/10.1038/s41598-018-25603-5

Oddo A , Peng B , Tong ZQ , et al. , 2019 . Advances in microfluidic blood‒brain barrier (BBB) models . Trends Biotechnol , 37 ( 12 ): 1295 - 1314 . https://doi.org/10.1016/j.tibtech.2019.04.006 https://doi.org/10.1016/j.tibtech.2019.04.006

Pandit R , Chen LY , Götz J , 2020 . The blood‒brain barrier: physiology and strategies for drug delivery . Adv Drug Deliv Rev , 165 - 166 : 1 - 14 . https://doi.org/10.1016/j.addr.2019.11.009 https://doi.org/10.1016/j.addr.2019.11.009

Pardridge WM , 2005 . The blood‒brain barrier: bottleneck in brain drug development . NeuroRx , 2 : 3 - 14 . https://doi.org/10.1602/neurorx.2.1.3 https://doi.org/10.1602/neurorx.2.1.3

Parkes LM , Tofts PS , 2002 . Improved accuracy of human cerebral blood perfusion measurements using arterial spin labeling: accounting for capillary water permeability . Magn Reson Med , 48 ( 1 ): 27 - 41 . https://doi.org/10.1002/mrm.10180 https://doi.org/10.1002/mrm.10180

Poon CT , Shah K , Lin C , et al. , 2018 . Time course of focused ultrasound effects on β-amyloid plaque pathology in the TgCRND8 mouse model of Alzheimer’s disease . Sci Rep , 8 : 14061 . https://doi.org/10.1038/s41598-018-32250-3 https://doi.org/10.1038/s41598-018-32250-3

Qin W , Li HH , Chen JL , et al. , 2025 . Amphiphilic hemicyanine molecular probes crossing the blood-brain barrier for intracranial optical imaging of glioblastoma . Sci Adv , 11 : eadq5816 . https://doi.org/10.1126/sciadv.adq5816 https://doi.org/10.1126/sciadv.adq5816

Raja R , Rosenberg GA , Caprihan A , 2018 . MRI measurements of blood‒brain barrier function in dementia: a review of recent studies . Neuropharmacology , 134 : 259 - 271 . https://doi.org/10.1016/j.neuropharm.2017.10.034 https://doi.org/10.1016/j.neuropharm.2017.10.034

Rollins ZA , Cheng AC , Metwally E , 2024 . MolPROP: molecular property prediction with multimodal language and graph fusion . J Cheminform , 16 : 56 . https://doi.org/10.1186/s13321-024-00846-9 https://doi.org/10.1186/s13321-024-00846-9

Rubin LL , Hall DE , Porter S , et al. , 1991 . A cell culture model of the blood‒brain barrier . J Cell Biol , 115 ( 6 ): 1725 - 1735 . https://doi.org/10.1083/jcb.115.6.1725 https://doi.org/10.1083/jcb.115.6.1725

Saxena D , Sharma A , Siddiqui MH , et al. , 2019 . Blood brain barrier permeability prediction using machine learning techniques: an update . Curr Pharm Biotechnol , 20 ( 14 ): 1163 - 1171 . https://doi.org/10.2174/1389201020666190821145346 https://doi.org/10.2174/1389201020666190821145346

Schurhoff N , Toborek M , 2023 . Circadian rhythms in the blood‒brain barrier: impact on neurological disorders and stress responses . Mol Brain , 16 : 5 . https://doi.org/10.1186/s13041-023-00997-0 https://doi.org/10.1186/s13041-023-00997-0

Segarra M , Aburto MR , Acker-Palmer A , 2021 . Blood‒brain barrier dynamics to maintain brain homeostasis . Trends Neurosci , 44 ( 5 ): 393 - 405 . https://doi.org/10.1016/j.tins.2020.12.002 https://doi.org/10.1016/j.tins.2020.12.002

Shaker B , Yu MS , Song JS , et al. , 2021 . LightBBB: computational prediction model of blood‒brain-barrier penetration based on LightGBM . Bioinformatics , 37 ( 8 ): 1135 - 1139 . https://doi.org/10.1093/bioinformatics/btaa918 https://doi.org/10.1093/bioinformatics/btaa918

Shang BL , Wang T , Zhao SL , et al. , 2024 . Higher blood‒brain barrier permeability in patients with major depressive disorder identified by DCE-MRI imaging . Psychiatry Res Neuroimaging , 337 : 111761 . https://doi.org/10.1016/j.pscychresns.2023.111761 https://doi.org/10.1016/j.pscychresns.2023.111761

Shumer-Elbaz M , Ad-El N , Chulanova Y , et al. , 2025 . Low-frequency ultrasound-mediated blood‒brain barrier opening enables non-invasive lipid nanoparticle RNA delivery to glioblastoma . J Control Release , 385 : 114018 . https://doi.org/10.1016/j.jconrel.2025.114018 https://doi.org/10.1016/j.jconrel.2025.114018

Siegel MJ , Kaza RK , Bolus DN , et al. , 2016 . White paper of the Society of Computed Body Tomography and magnetic resonance on dual-energy CT, Part 1: technology and terminology . J Comput Assist Tomogr , 40 ( 6 ): 841 - 845 . https://doi.org/10.1097/rct.0000000000000531 https://doi.org/10.1097/rct.0000000000000531

Simonneau C , Duschmalé M , Gavrilov A , et al. , 2021 . Investigating receptor-mediated antibody transcytosis using blood‒brain barrier organoid arrays . Fluids Barriers CNS , 18 : 43 . https://doi.org/10.1186/s12987-021-00276-x https://doi.org/10.1186/s12987-021-00276-x

Sivandzade F , Cucullo L , 2018 . In-vitro blood‒brain barrier modeling: a review of modern and fast-advancing technologies . J Cereb Blood Flow Metab , 38 ( 10 ): 1667 - 1681 . https://doi.org/10.1177/0271678x18788769 https://doi.org/10.1177/0271678x18788769

Sonninen TM , Peltonen S , Kälvälä S , et al. , 2025 . From inserts to chips: microfluidic culture and 3D astrocyte co-culture drive functional and transcriptomic changes in hiPSC-derived endothelial cells . Fluids Barriers CNS , 22 : 58 . https://doi.org/10.1186/s12987-025-00672-7 https://doi.org/10.1186/s12987-025-00672-7

Srinivasan B , Kolli AR , Esch MB , et al. , 2015 . TEER measurement techniques for in vitro barrier model systems . J Lab Autom , 20 ( 2 ): 107 - 126 . https://doi.org/10.1177/2211068214561025 https://doi.org/10.1177/2211068214561025

St . Lawrence KS , Frank JA , McLaughlin AC, 2000 . Effect of restricted water exchange on cerebral blood flow values calculated with arterial spin tagging: a theoretical investigation. Magn Reson Med, 44 ( 3 ): 440 - 449 . https://doi.org/10.1002/1522-2594(200009)44:3<440::AID-MRM15>3.0.CO;2-6 https://doi.org/10.1002/1522-2594(200009)44:3<440::AID-MRM15>3.0.CO;2-6

St . Lawrence KS , Owen D , Wang DJJ, 2012 . A two-stage approach for measuring vascular water exchange and arterial transit time by diffusion-weighted perfusion MRI. Magn Reson Med, 67 ( 5 ): 1275 - 1284 . https://doi.org/10.1002/mrm.23104 https://doi.org/10.1002/mrm.23104

Stamatovic SM , Johnson AM , Keep RF , et al. , 2016 . Junctional proteins of the blood‒brain barrier: new insights into function and dysfunction . Tissue Barriers , 4 ( 1 ): e1154641 . https://doi.org/10.1080/21688370.2016.1154641 https://doi.org/10.1080/21688370.2016.1154641

Stanness KA , Westrum LE , Fornaciari E , et al. , 1997 . Morphological and functional characterization of an in vitro blood‒brain barrier model . Brain Res , 771 ( 2 ): 329 - 342 . https://doi.org/10.1016/S0006-8993(97)00829-9 https://doi.org/10.1016/S0006-8993(97)00829-9

Sun JD , Song S , 2024 . Advances in modeling permeability and selectivity of the blood‒brain barrier using microfluidics . Microfluid Nanofluidics , 28 ( 7 ): 44 . https://doi.org/10.1007/s10404-024-02741-z https://doi.org/10.1007/s10404-024-02741-z

Tevosyan A , Khondkaryan L , Khachatrian H , et al. , 2022 . Improving VAE based molecular representations for compound property prediction . J Cheminform , 14 : 69 . https://doi.org/10.1186/s13321-022-00648-x https://doi.org/10.1186/s13321-022-00648-x

Toyohara J , 2016 . Importance of P-gp PET imaging in pharmacology . Curr Pharm Des , 22 ( 38 ): 5830 - 5836 . https://doi.org/10.2174/1381612822666160804092258 https://doi.org/10.2174/1381612822666160804092258

Turowski P , Kenny BA , 2015 . The blood‒brain barrier and methamphetamine: open sesame? Front Neurosci , 9 : 156 . https://doi.org/10.3389/fnins.2015.00156 https://doi.org/10.3389/fnins.2015.00156

van de Haar HJ , Burgmans S , Jansen JFA , et al. , 2016 . Blood‒brain barrier leakage in patients with early Alzheimer disease . Radiology , 281 ( 2 ): 527 - 535 . https://doi.org/10.1148/radiol.2016152244 https://doi.org/10.1148/radiol.2016152244

van der Helm MW , Odijk M , Frimat JP , et al. , 2016 . Direct quantification of transendothelial electrical resistance in organs-on-chips . Biosens Bioelectron , 85 : 924 - 929 . https://doi.org/10.1016/j.bios.2016.06.014 https://doi.org/10.1016/j.bios.2016.06.014

Verstappen D , de Jong JJA , Voorter PHM , et al. , 2025 . DCE-MRI reveals spatial pattern in heterogeneous blood‒brain barrier leakage within white matter in cerebral small vessel disease . J Cereb Blood Flow Metab , 45 ( 11 ): 2104 - 2114 . https://doi.org/10.1177/0271678x251364151 https://doi.org/10.1177/0271678x251364151

Vorbrodt AW , Dobrogowska DH , 2003 . Molecular anatomy of intercellular junctions in brain endothelial and epithelial barriers: electron microscopist’s view . Brain Res Rev , 42 ( 3 ): 221 - 242 . https://doi.org/10.1016/S0165-0173(03)00177-2 https://doi.org/10.1016/S0165-0173(03)00177-2

Wang D , Chen FL , Han ZL , et al. , 2021 . Relationship between amyloid-β deposition and blood‒brain barrier dysfunction in Alzheimer’s disease . Front Cell Neurosci , 15 : 695479 . https://doi.org/10.3389/fncel.2021.695479 https://doi.org/10.3389/fncel.2021.695479

Wang GX , Zhou YY , Yu CH , et al. , 2024 . Intravital photoacoustic brain stimulation with high-precision . J Biomed Opt , 29 ( S1 ): S11520 . https://doi.org/10.1117/1.jbo.29.s1.s11520 https://doi.org/10.1117/1.jbo.29.s1.s11520

Wang JJ , Fernández-Seara MA , Wang SM , et al. , 2007 . When perfusion meets diffusion: in vivo measurement of water permeability in human brain . J Cereb Blood Flow Metab , 27 ( 4 ): 839 - 849 . https://doi.org/10.1038/sj.jcbfm.9600398 https://doi.org/10.1038/sj.jcbfm.9600398

Wang SC , Shi H , Wang LS , et al. , 2022 . Photostable small-molecule NIR-II fluorescent scaffolds that cross the blood‒brain barrier for noninvasive brain imaging . J Am Chem Soc , 144 ( 51 ): 23668 - 23676 . https://doi.org/10.1021/jacs.2c11223 https://doi.org/10.1021/jacs.2c11223

Wang X , Li P , Ding Q , et al. , 2019 . Observation of acetylcholinesterase in stress-induced depression phenotypes by two-photon fluorescence imaging in the mouse brain . J Am Chem Soc , 141 ( 5 ): 2061 - 2068 . https://doi.org/10.1021/jacs.8b11414 https://doi.org/10.1021/jacs.8b11414

Wang XB , Hou Y , Ai XP , et al. , 2020 . Potential applications of microfluidics based blood brain barrier (BBB)-on-chips for in vitro drug development . Biomed Pharmacother , 132 : 110822 . https://doi.org/10.1016/j.biopha.2020.110822 https://doi.org/10.1016/j.biopha.2020.110822

Weksler B , Romero IA , Couraud PO , 2013 . The hCMEC/D3 cell line as a model of the human blood brain barrier . Fluids Barriers CNS , 10 : 16 . https://doi.org/10.1186/2045-8118-10-16 https://doi.org/10.1186/2045-8118-10-16

Wen NF , Liu GQ , Zhang J , et al. , 2022 . A fingerprints based molecular property prediction method using the BERT model . J Cheminform , 14 : 71 . https://doi.org/10.1186/s13321-022-00650-3 https://doi.org/10.1186/s13321-022-00650-3

Wevers NR , Kasi DG , Gray T , et al. , 2018 . A perfused human blood‒brain barrier on-a-chip for high-throughput assessment of barrier function and antibody transport . Fluids Barriers CNS , 15 : 23 . https://doi.org/10.1186/s12987-018-0108-3 https://doi.org/10.1186/s12987-018-0108-3

Winklhofer S , de Martini IV , Nern C , et al. , 2017 . Dual-energy computed tomography in stroke imaging: technical and clinical considerations of virtual noncontrast images for detection of the hyperdense artery sign . J Comput Assist Tomogr , 41 ( 6 ): 843 - 848 . https://doi.org/10.1097/rct.0000000000000638 https://doi.org/10.1097/rct.0000000000000638

Withnall M , Lindelöf E , Engkvist O , et al. , 2020 . Building attention and edge message passing neural networks for bioactivity and physical-chemical property prediction . J Cheminf , 12 : 1 . https://doi.org/10.1186/s13321-019-0407-y https://doi.org/10.1186/s13321-019-0407-y

Wu D , Chen Q , Chen XJ , et al. , 2023 . The blood‒brain barrier: structure, regulation and drug delivery . Signal Transduct Target Ther , 8 : 217 . https://doi.org/10.1038/s41392-023-01481-w https://doi.org/10.1038/s41392-023-01481-w

Xiong CH , Yu ZY , Yin Y , et al. , 2025 . Longitudinal changes of blood‒brain barrier and transcytolemmal water exchange permeability in Alzheimer’s disease mice: a non-contrast MRI study . Neuroimage , 310 : 121141 . https://doi.org/10.1016/j.neuroimage.2025.121141 https://doi.org/10.1016/j.neuroimage.2025.121141

Xu HL , Li R , Duan YX , et al. , 2017 . Quantitative assessment on blood‒brain barrier permeability of acute spontaneous intracerebral hemorrhage in basal ganglia: a CT perfusion study . Neuroradiology , 59 ( 7 ): 677 - 684 . https://doi.org/10.1007/s00234-017-1852-9 https://doi.org/10.1007/s00234-017-1852-9

Yang G , Pan F , Parkhurst CN , et al. , 2010 . Thinned-skull cranial window technique for long-term imaging of the cortex in live mice . Nat Protoc , 5 : 201 - 208 . https://doi.org/10.1038/nprot.2009.222 https://doi.org/10.1038/nprot.2009.222

Yang JY , Shin DS , Jeong M , et al. , 2024 . Evaluation of drug blood‒brain-barrier permeability using a microfluidic chip . Pharmaceutics , 16 ( 5 ): 574 . https://doi.org/10.3390/pharmaceutics16050574 https://doi.org/10.3390/pharmaceutics16050574

Yang XY , Wang QZ , Cao EH , 2020 . Structure of the human cation-chloride cotransporter NKCC1 determined by single-particle electron cryo-microscopy . Nat Commun , 11 : 1016 . https://doi.org/10.1038/S41467-020-14790-3 https://doi.org/10.1038/S41467-020-14790-3

Yuan YX , Zheng F , Zhan CG , 2018 . Improved prediction of blood‒brain barrier permeability through machine learning with combined use of molecular property-based descriptors and fingerprints . AAPS J , 20 ( 3 ): 54 . https://doi.org/10.1208/s12248-018-0215-8 https://doi.org/10.1208/s12248-018-0215-8

Zhang CE , Wong SM , Uiterwijk R , et al. , 2019 . Blood‒brain barrier leakage in relation to white matter hyperintensity volume and cognition in small vessel disease and normal aging . Brain Imaging Behav , 13 ( 2 ): 389 - 395 . https://doi.org/10.1007/s11682-018-9855-7 https://doi.org/10.1007/s11682-018-9855-7

Zhang HT , Kang DH , Piantino M , et al. , 2023 . Rapid quantification of microvessels of three-dimensional blood‒brain barrier model using optical coherence tomography and deep learning algorithm . Biosensors , 13 ( 8 ): 818 . https://doi.org/10.3390/bios13080818 https://doi.org/10.3390/bios13080818

Zhang SS , Gong P , Zhang JS , et al. , 2020 . Specific frequency electroacupuncture stimulation transiently enhances the permeability of the blood‒brain barrier and induces tight junction changes . Front Neurosci , 14 : 582324 . https://doi.org/10.3389/fnins.2020.582324 https://doi.org/10.3389/fnins.2020.582324

Zhao Z , Nelson AR , Betsholtz C , et al. , 2015 . Establishment and dysfunction of the blood‒brain barrier . Cell , 163 ( 5 ): 1064 - 1078 . https://doi.org/10.1016/j.cell.2015.10.067 https://doi.org/10.1016/j.cell.2015.10.067

Zheng YY , Chen XJ , Wang Y , et al. , 2024 . Phenolic-enabled nanotechnology: a new strategy for central nervous system disease therapy . J Zhejiang Univ-Sci B (Biomed & Biotechnol) , 25 ( 10 ): 890 - 913 . https://doi.org/10.1631/jzus.B2300839 https://doi.org/10.1631/jzus.B2300839

Views

Downloads

CSCD

Tools

Publicity Resources

Programmable DNAzyme nanocatalysts for tumor immunometabolic modulation

Emerging point-of-care technologies for bacterial pathogen detection

Selenocystine-based fluorescence assay combined with structural prediction for functional analysis of cystine transporter variants in cystinuria

Dual-functional nanoplatform for simultaneous degradation of circRNA CDR1as and real-time monitoring of miR-7 in live cells

Intelligent biosensing and point-of-care testing: from molecular recognition to decentralized precision care

Related Author

No data

Related Institution

No data

Address：Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou, China Postal code：310027
Tel：+86-571-87952783 Email：cjzhang@zju.edu.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰