How does the brain rid itself of waste products? Other organs in the body achieve this via a system called the lymphatic system. A network of lymphatic vessels extends throughout the body in a pattern similar to that of blood vessels. Waste products from cells, plus bacteria, viruses and excess fluids drain out of the body’s tissues into lymphatic vessels, which transfer them to the bloodstream. Blood vessels then carry the waste products to the kidneys, which filter them out for excretion. Lymphatic vessels are also a highway for circulation of white blood cells, which fight infections, and are therefore an important part of the immune system.

Unlike other organs, the brain does not contain lymphatic vessels. So how does it remove waste? Some of the brain’s waste products enter the fluid that bathes and protects the brain – the cerebrospinal fluid – before being disposed of via the bloodstream. However, recent studies in rodents have also shown the presence of lymphatic vessels inside the outer membrane surrounding the brain, the dura mater.

Absinta, Ha et al. now show that the dura mater of people and marmoset monkeys contains lymphatic vessels too. Spotting lymphatic vessels is challenging because they resemble blood vessels, which are much more numerous. In addition, Absinta, Ha et al. found a way to visualize the lymphatic vessels in the dura mater using brain magnetic resonance imaging, and could confirm that lymphatic vessels are present in autopsy tissue using special staining methods.

For magnetic resonance imaging, monkeys and human volunteers received an injection of a dye-like substance called gadolinium, which travels via the bloodstream to the brain. In the dura mater, gadolinium leaks out of blood vessels and collects inside lymphatic vessels, which show up as bright white areas on brain scans. To confirm that the white areas were lymphatic vessels, the experiment was repeated using a different dye that does not leak out of blood vessels. As expected, the signals observed in the previous brain scans did not appear.

By visualizing the lymphatic system, this technique makes it possible to study how the brain removes waste products and circulates white blood cells, and to examine whether this process is impaired in aging or disease.

Recent reports (Aspelund et al., 2015; Louveau et al., 2015b) described the existence of a network of true lymphatic vessels within the mammalian dura mater that runs alongside blood vessels, notably the superior sagittal and transverse sinuses. The dural lymphatic vessels display typical immunohistochemical markers that identify lymphatic vessels elsewhere in the body. They provide an alternate conduit for drainage of immune cells and cerebrospinal fluid (CSF) from the brain, beyond previously described pathways of flow: via arachnoid granulations into the dural venous sinuses, and via the cribriform plate into the ethmoid region (Weller et al., 2009). Although early reports, based on injections of India ink into the cisterna magna of the rat, suggested that the dural pathway accounts for only a minority of the drainage (Kida et al., 1993), the more recent studies (Aspelund et al., 2015; Louveau et al., 2015b), which are based on injections of fluorescent tracers and in vivo microscopy, indicate that the dural system may be substantially more important for drainage of macromolecules and immune cells than previously realized.

Whether a similar network of dural lymphatics is present in primates remains unknown. Moreover, noninvasive visualization of the dural lymphatics – a necessary first step to understanding their normal physiology and potential aberrations in neurological diseases – has not been reported. We therefore verified pathologically the existence of a dural lymphatic network in human and nonhuman primates (common marmoset monkeys) and evaluated two magnetic resonance imaging (MRI) techniques that might enable its visualization in vivo. First, the T2-weighted fluid-attenuation inversion recovery (T2-FLAIR) pulse sequence, which is the clinical standard for detecting lesions within the brain parenchyma, is highly sensitive to the presence of gadolinium-based contrast agents in the CSF (Mamourian et al., 2000; Mathews et al., 1999; Absinta et al., 2015). Second, ‘black-blood’ imaging sequences, which are typically used for measurement of vascular wall thickness or detection of atherosclerotic plaque, are tuned to darken the contents of blood vessels (even when they contain a gadolinium-based contrast agent), but in the process the images may highlight vessels with other contents and flow properties (Mandell et al., 2017). For comparison, we also acquired a postcontrast T1-weighted Magnetization Prepared Rapid Acquisition of Gradient Echoes (MPRAGE) MRI sequence, which is widely implemented for structural brain imaging and depicts avid enhancement of dura mater and blood vessels, but which would not be expected to discriminate lymphatic vessels.

Cerebral blood vessels have a highly regulated blood-brain barrier, protecting the neuropil from many contents of the circulating blood. Under physiological conditions, the blood-brain barrier prevents gadolinium-based chelates in standard clinical use from passing into the Virchow-Robin perivascular spaces and parenchyma, so that these structures do not enhance on MRI. On the other hand, dural blood vessels lack a blood-meningeal barrier, enabling leakage of circulating fluids and small substances, including gadolinium-based compounds. This explains the thin, though often incomplete, dural enhancement that is seen on conventional T1-weighted MRI scans under physiological conditions (Figure 1), as well as its abnormal diffuse or localized thickening in a variety of pathological conditions (Smirniotopoulos et al., 2007; Antony et al., 2015). Using high-resolution (in-plane resolution 270 × 270 μm or finer) T2-FLAIR and T1-weighted black-blood MRI images, obtained after the intravenous injection of standard FDA-approved contrast material (gadobutrol), we were able to visualize the collection of interstitial gadolinium within dural lymphatic vessels (maximum apparent diameter ~1 mm) in 5/5 human healthy volunteers and 3/3 common marmoset monkeys (Figure 1). Our results suggest that in the dura, similar to many other organs throughout the body, small intravascular molecules extravasate into the interstitium and then, under a hydrostatic pressure gradient, collect into lymphatic capillaries through a loose lymphatic endothelium (Sharma et al., 2008).

Figure 1 with 1 supplement see all

Download asset Open asset

To further test this hypothesis, meningeal lymphatics were also assessed using a second gadolinium-based contrast agent, gadofosveset, a blood-pool contrast agent suitable for angiography (Lauffer et al., 1998). Gadofosveset binds reversibly to serum albumin, increasing its molecular weight from 0.9 to 67 kDa. Under physiological conditions, albumin has a low transcapillary exchange rate into the interstitial compartment, estimated to be on the order of 5% per hour, which explains the propensity of gadofosveset to remain within blood vessels (Richardson et al., 2015). In both species, gadofosveset did not reveal dural lymphatics, especially on T1-black blood images (Figure 2 and Figure 2—figure supplement 1). As expected, on T1-weighted MPRAGE images, gadofosveset provided superior intravascular enhancement, in both meningeal and parenchymal blood vessels, compared to gadobutrol (Figure 2).

Figure 2 with 1 supplement see all

Download asset Open asset

On 3D-rendering of subtraction MRI images (Videos 1–2, Figure 1—figure supplement 1), dural lymphatics are seen running parallel to the dural venous sinuses, especially the superior sagittal and straight sinuses, and alongside branches of the middle meningeal artery. The topography of the meningeal lymphatics fits with the previously described network in rodents as well as our neuropathological data (Figures 3 and 4). It is worth noting that the lymphatics visualized by MRI are large slow-flow lymphatic ducts, whereas blind-ending and small lymphatic capillaries, clearly seen by histopathology (Figure 3 and Figure 3—figure supplement 1), are unlikely to be revealed by MRI. The induction of experimental autoimmune encephalomyelitis (EAE) did not affect detection of dural lymphatic vessel in either of the two animals that we tested (not shown).

Figure 3 with 2 supplements see all

Download asset Open asset

Figure 3—source data 1

Table of human tissue sampling.

https://doi.org/10.7554/eLife.29738.010

Download elife-29738-fig3-data1-v2.docx

Figure 4 with 1 supplement see all

Download asset Open asset

Figure 4—source data 1

Table of marmoset tissue sampling.

https://doi.org/10.7554/eLife.29738.013

Download elife-29738-fig4-data1-v2.docx

Video 1

Download asset

Video 2

Download asset

To support our in vivo imaging results, we further investigated the existence and topography of lymphatics in coronal and longitudinal sections of human and marmoset dura mater. To accomplish this, we tested a variety of putative lymphatic endothelial markers and found that selective double immunostaining for D2-40 podoplanin/CD31 and for PROX1/CD31 was the most effective strategy in discriminating lymphatic vs. venous blood vessels in dura samples – a challenging task since lymphatics sprout from transdifferentiation of venous endothelium (Ny et al., 2005; Yaniv et al., 2006; Srinivasan et al., 2007; Aspelund et al., 2014; Lowe et al., 2015) and persistently share some endothelial markers. A branched network of lymphatics was clearly seen within the dura mater. On D2-40 podoplanin/CD31 double staining, we identified a total of 93 human dural lymphatics; most were collapsed, explaining the large range of maximum transverse diameters (range = 7–842 μm, mean = 125 μm, standard deviation = 161 μm). The density of dural lymphatics was higher around the venous sinuses than in more lateral areas of the dura, and higher within the meningeal layer than the periosteal layer of the dura. As expected, red blood cells were not seen within lymphatics. In marmosets, direct comparison between in vivo MRI and histopathology was performed (Absinta et al., 2014; Guy et al., 2016; Luciano et al., 2016). As shown in Figure 4 and Figure 4—figure supplement 1, the three dural vessels detected on coronal postcontrast T2-FLAIR and on subtraction images colocalize with three clusters of dural cells expressing the full panel of lymphatic endothelial markers (LYVE-1, D2-40 podoplanin, PROX1, COUP-TFII) and CCL21, a chemokine implicated in lymphatic transmigration.

In the ongoing debate about the precise localization of lymphatics within the meninges (either completely within the dura or ‘shared’ between the dura and the arachnoid) (Kipnis, 2016; Raper et al., 2016), our pathological data clearly show that at least some lymphatics are contained entirely within the dura (Figures 3 and 4). On limited evaluation, we were unable to visualize lymphatics within the leptomeninges, but additional dedicated studies, ideally with nonconventional tissue-preparation methods, are warranted to fully explore this possibility. A comprehensive map of the meningeal lymphatic network would have implications for unraveling the ways in which the meningeal lymphatics participate in waste clearance and in immune cell trafficking within the central nervous system (Louveau et al., 2015a; Kipnis, 2016; Raper et al., 2016).

In inflammatory pathological conditions, cellular migration toward the dural lymphatics might be profoundly enhanced by specific signaling and lymphatic plasticity (Alitalo et al., 2005; Kim et al., 2012; Stacker et al., 2014). Noteworthy in this context are clusters of extravascular CD3+ lymphocytes and CD68+ phagocytic meningeal macrophages that we observed in the dura of several multiple sclerosis autopsies (not shown), confirming intense immune cell trafficking and communication. Indeed, without proper normative comparison, we cannot rule out that the extensive presence of small lymphatics observed in multiple sclerosis dura samples is the result of inflammation-mediated lymphoangiogenesis. On the other hand, lymphatic dysfunction might impair waste clearance in neurodegenerative diseases and aging, in line with the recently captured deposition of β-amyloid in human dura in elderly people (Kovacs et al., 2016).

Differently from experiments implementing injections of tracers within brain structures, here we aimed primarily to image dural lymphatic vessels in human and nonhuman primates, but we could not prove whether dural lymphatic vessels drain immune cells, CSF, or other substances from the brain to deep cervical lymph nodes, nor could we assess any link with the glymphatic system (Iliff et al., 2012; Xie et al., 2013; Iliff et al., 2013). Such an analysis would probably require injection of specific MRI-detectable tracers and acquisition of MRI time-series (not thoroughly explored in the current work), an important future research direction for the nonhuman primate work.

Overall, our data clearly and consistently demonstrate the existence of lymphatic vessels within the dura mater of human and nonhuman primates. Together with recent studies in rodents, our results show that the meningeal lymphatic system is evolutionarily conserved in mammals and confirm, after exactly two centuries, what the Italian anatomist Paolo Mascagni speculated were lymphatic vessels at the surface of human brain (Mascagni and Bellini, 1816). The ability to image the meningeal lymphatics noninvasively immediately suggests the possibility of studying potential abnormalities in human neurological disorders.

1. 1. Absinta M
   2. Nair G
   3. Filippi M
   4. Ray-Chaudhury A
   5. Reyes-Mantilla MI
   6. Pardo CA
   7. Reich DS

   (2014) Postmortem magnetic resonance imaging to guide the pathologic cut: individualized, 3-dimensionally printed cutting boxes for fixed brains

   Journal of Neuropathology and Experimental Neurology 73:780–788.

   https://doi.org/10.1097/NEN.0000000000000096

   • PubMed
   • Google Scholar
2. 1. Absinta M
   2. Vuolo L
   3. Rao A
   4. Nair G
   5. Sati P
   6. Cortese IC
   7. Ohayon J
   8. Fenton K
   9. Reyes-Mantilla MI
   10. Maric D
   11. Calabresi PA
   12. Butman JA
   13. Pardo CA
   14. Reich DS

   (2015) Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis

   Neurology 85:18–28.

   https://doi.org/10.1212/WNL.0000000000001587

   • PubMed
   • Google Scholar
3. 1. Alitalo K
   2. Tammela T
   3. Petrova TV

   (2005) Lymphangiogenesis in development and human disease

   Nature 438:946–953.

   https://doi.org/10.1038/nature04480

   • PubMed
   • Google Scholar
4. 1. Antony J
   2. Hacking C
   3. Jeffree RL

   (2015) Pachymeningeal enhancement-a comprehensive review of literature

   Neurosurgical Review 38:649–659.

   https://doi.org/10.1007/s10143-015-0646-y

   • PubMed
   • Google Scholar
5. 1. Aspelund A
   2. Tammela T
   3. Antila S
   4. Nurmi H
   5. Leppänen VM
   6. Zarkada G
   7. Stanczuk L
   8. Francois M
   9. Mäkinen T
   10. Saharinen P
   11. Immonen I
   12. Alitalo K

   (2014) The Schlemm's canal is a VEGF-C/VEGFR-3-responsive lymphatic-like vessel

   Journal of Clinical Investigation 124:3975–3986.

   https://doi.org/10.1172/JCI75395

   • PubMed
   • Google Scholar
6. 1. Aspelund A
   2. Antila S
   3. Proulx ST
   4. Karlsen TV
   5. Karaman S
   6. Detmar M
   7. Wiig H
   8. Alitalo K

   (2015) A dural lymphatic vascular system that drains brain interstitial fluid and macromolecules

   The Journal of Experimental Medicine 212:991–999.

   https://doi.org/10.1084/jem.20142290

   • PubMed
   • Google Scholar
7. 1. Gaitán MI
   2. Maggi P
   3. Wohler J
   4. Leibovitch E
   5. Sati P
   6. Calandri IL
   7. Merkle H
   8. Massacesi L
   9. Silva AC
   10. Jacobson S
   11. Reich DS

   (2014) Perivenular brain lesions in a primate multiple sclerosis model at 7-tesla magnetic resonance imaging

   Multiple Sclerosis Journal 20:64–71.

   https://doi.org/10.1177/1352458513492244

   • PubMed
   • Google Scholar
8. 1. Guy JR
   2. Sati P
   3. Leibovitch E
   4. Jacobson S
   5. Silva AC
   6. Reich DS

   (2016) Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets

   Journal of Neuroscience Methods 257:55–63.

   https://doi.org/10.1016/j.jneumeth.2015.09.002

   • PubMed
   • Google Scholar
9. 1. Iliff JJ
   2. Wang M
   3. Liao Y
   4. Plogg BA
   5. Peng W
   6. Gundersen GA
   7. Benveniste H
   8. Vates GE
   9. Deane R
   10. Goldman SA
   11. Nagelhus EA
   12. Nedergaard M

   (2012) A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β

   Science Translational Medicine 4:147ra111.

   https://doi.org/10.1126/scitranslmed.3003748

   • PubMed
   • Google Scholar
10. 1. Iliff JJ
    2. Lee H
    3. Yu M
    4. Feng T
    5. Logan J
    6. Nedergaard M
    7. Benveniste H

    (2013) Brain-wide pathway for waste clearance captured by contrast-enhanced MRI

    Journal of Clinical Investigation 123:1299–1309.

    https://doi.org/10.1172/JCI67677

    • PubMed
    • Google Scholar
11. 1. Kida S
    2. Pantazis A
    3. Weller RO

    (1993) CSF drains directly from the subarachnoid space into nasal lymphatics in the rat. Anatomy, histology and immunological significance

    Neuropathology and Applied Neurobiology 19:480–488.

    https://doi.org/10.1111/j.1365-2990.1993.tb00476.x

    • PubMed
    • Google Scholar
12. 1. Kim H
    2. Kataru RP
    3. Koh GY

    (2012) Regulation and implications of inflammatory lymphangiogenesis

    Trends in Immunology 33:350–356.

    https://doi.org/10.1016/j.it.2012.03.006

    • PubMed
    • Google Scholar
13. 1. Kipnis J

    (2016) Multifaceted interactions between adaptive immunity and the central nervous system

    Science 353:766–771.

    https://doi.org/10.1126/science.aag2638

    • PubMed
    • Google Scholar
14. 1. Kovacs GG
    2. Lutz MI
    3. Ricken G
    4. Ströbel T
    5. Höftberger R
    6. Preusser M
    7. Regelsberger G
    8. Hönigschnabl S
    9. Reiner A
    10. Fischer P
    11. Budka H
    12. Hainfellner JA

    (2016) Dura mater is a potential source of Aβ seeds

    Acta Neuropathologica 131:911–923.

    https://doi.org/10.1007/s00401-016-1565-x

    • PubMed
    • Google Scholar
15. 1. Lauffer RB
    2. Parmelee DJ
    3. Dunham SU
    4. Ouellet HS
    5. Dolan RP
    6. Witte S
    7. McMurry TJ
    8. Walovitch RC

    (1998) MS-325: albumin-targeted contrast agent for MR angiography

    Radiology 207:529–538.

    https://doi.org/10.1148/radiology.207.2.9577506

    • PubMed
    • Google Scholar
16. 1. Louveau A
    2. Harris TH
    3. Kipnis J

    (2015a) Revisiting the Mechanisms of CNS Immune Privilege

    Trends in Immunology 36:569–577.

    https://doi.org/10.1016/j.it.2015.08.006

    • PubMed
    • Google Scholar
17. 1. Louveau A
    2. Smirnov I
    3. Keyes TJ
    4. Eccles JD
    5. Rouhani SJ
    6. Peske JD
    7. Derecki NC
    8. Castle D
    9. Mandell JW
    10. Lee KS
    11. Harris TH
    12. Kipnis J

    (2015b) Structural and functional features of central nervous system lymphatic vessels

    Nature 523:337–341.

    https://doi.org/10.1038/nature14432

    • PubMed
    • Google Scholar
18. 1. Lowe KL
    2. Finney BA
    3. Deppermann C
    4. Hägerling R
    5. Gazit SL
    6. Frampton J
    7. Buckley C
    8. Camerer E
    9. Nieswandt B
    10. Kiefer F
    11. Watson SP

    (2015) Podoplanin and CLEC-2 drive cerebrovascular patterning and integrity during development

    Blood 125:3769–3777.

    https://doi.org/10.1182/blood-2014-09-603803

    • PubMed
    • Google Scholar
19. 1. Luciano NJ
    2. Sati P
    3. Nair G
    4. Guy JR
    5. Ha SK
    6. Absinta M
    7. Chiang WY
    8. Leibovitch EC
    9. Jacobson S
    10. Silva AC
    11. Reich DS

    (2016) Utilizing 3D printing technology to merge mri with histology: a protocol for brain sectioning

    Journal of Visualized Experiments 118:.

    https://doi.org/10.3791/54780

    • PubMed
    • Google Scholar
20. 1. Mamourian AC
    2. Hoopes PJ
    3. Lewis LD

    (2000)

    Visualization of intravenously administered contrast material in the CSF on fluid-attenuated inversion-recovery MR images: an in vitro and animal-model investigation

    AJNR. American Journal of Neuroradiology 21:105–111.

    • PubMed
    • Google Scholar
21. 1. Mandell DM
    2. Mossa-Basha M
    3. Qiao Y
    4. Hess CP
    5. Hui F
    6. Matouk C
    7. Johnson MH
    8. Daemen MJ
    9. Vossough A
    10. Edjlali M
    11. Saloner D
    12. Ansari SA
    13. Wasserman BA
    14. Mikulis DJ
    15. Vessel Wall Imaging Study Group of the American Society of Neuroradiology

    (2017) Intracranial Vessel Wall MRI: Principles and Expert Consensus Recommendations of the American Society of Neuroradiology

    American Journal of Neuroradiology 38:218–229.

    https://doi.org/10.3174/ajnr.A4893

    • PubMed
    • Google Scholar
22. Book

    1. Mascagni P
    2. Bellini GB

    (1816)

    Istoria Completa Dei Vasi Linfatici, Vol. II

    Florence: Presso Eusebio Pacini e Figlio.

    • Google Scholar
23. 1. Mathews VP
    2. Caldemeyer KS
    3. Lowe MJ
    4. Greenspan SL
    5. Weber DM
    6. Ulmer JL

    (1999) Brain: gadolinium-enhanced fast fluid-attenuated inversion-recovery MR imaging

    Radiology 211:257–263.

    https://doi.org/10.1148/radiology.211.1.r99mr25257

    • PubMed
    • Google Scholar
24. 1. Ny A
    2. Koch M
    3. Schneider M
    4. Neven E
    5. Tong RT
    6. Maity S
    7. Fischer C
    8. Plaisance S
    9. Lambrechts D
    10. Héligon C
    11. Terclavers S
    12. Ciesiolka M
    13. Kälin R
    14. Man WY
    15. Senn I
    16. Wyns S
    17. Lupu F
    18. Brändli A
    19. Vleminckx K
    20. Collen D
    21. Dewerchin M
    22. Conway EM
    23. Moons L
    24. Jain RK
    25. Carmeliet P

    (2005) A genetic Xenopus laevis tadpole model to study lymphangiogenesis

    Nature Medicine 11:998–1004.

    https://doi.org/10.1038/nm1285

    • PubMed
    • Google Scholar
25. 1. Raper D
    2. Louveau A
    3. Kipnis J

    (2016) How do meningeal lymphatic vessels drain the cns?

    Trends in Neurosciences 39:581–586.

    https://doi.org/10.1016/j.tins.2016.07.001

    • PubMed
    • Google Scholar
26. 1. Richardson OC
    2. Bane O
    3. Scott ML
    4. Tanner SF
    5. Waterton JC
    6. Sourbron SP
    7. Carroll TJ
    8. Buckley DL

    (2015) Gadofosveset-based biomarker of tissue albumin concentration: technical validation in vitro and feasibility in vivo

    Magnetic Resonance in Medicine 73:244–253.

    https://doi.org/10.1002/mrm.25128

    • PubMed
    • Google Scholar
27. 1. Sharma R
    2. Wendt JA
    3. Rasmussen JC
    4. Adams KE
    5. Marshall MV
    6. Sevick-Muraca EM

    (2008) New horizons for imaging lymphatic function

    Annals of the New York Academy of Sciences 1131:13–36.

    https://doi.org/10.1196/annals.1413.002

    • PubMed
    • Google Scholar
28. 1. Smirniotopoulos JG
    2. Murphy FM
    3. Rushing EJ
    4. Rees JH
    5. Schroeder JW

    (2007) Patterns of contrast enhancement in the brain and meninges

    RadioGraphics 27:525–551.

    https://doi.org/10.1148/rg.272065155

    • PubMed
    • Google Scholar
29. 1. Srinivasan RS
    2. Dillard ME
    3. Lagutin OV
    4. Lin FJ
    5. Tsai S
    6. Tsai MJ
    7. Samokhvalov IM
    8. Oliver G

    (2007)

    Lineage tracing demonstrates the venous origin of the mammalian lymphatic vasculature

    Genes & Development 21:2422–2432.

    • Google Scholar
30. 1. Stacker SA
    2. Williams SP
    3. Karnezis T
    4. Shayan R
    5. Fox SB
    6. Achen MG

    (2014) Lymphangiogenesis and lymphatic vessel remodelling in cancer

    Nature Reviews Cancer 14:159–172.

    https://doi.org/10.1038/nrc3677

    • PubMed
    • Google Scholar
31. 1. Weller RO
    2. Djuanda E
    3. Yow HY
    4. Carare RO

    (2009) Lymphatic drainage of the brain and the pathophysiology of neurological disease

    Acta Neuropathologica 117:1–14.

    https://doi.org/10.1007/s00401-008-0457-0

    • PubMed
    • Google Scholar
32. 1. Xie L
    2. Kang H
    3. Xu Q
    4. Chen MJ
    5. Liao Y
    6. Thiyagarajan M
    7. O'Donnell J
    8. Christensen DJ
    9. Nicholson C
    10. Iliff JJ
    11. Takano T
    12. Deane R
    13. Nedergaard M

    (2013) Sleep drives metabolite clearance from the adult brain

    Science 342:373–377.

    https://doi.org/10.1126/science.1241224

    • PubMed
    • Google Scholar
33. 1. Yaniv K
    2. Isogai S
    3. Castranova D
    4. Dye L
    5. Hitomi J
    6. Weinstein BM

    (2006) Live imaging of lymphatic development in the zebrafish

    Nature Medicine 12:711–716.

    https://doi.org/10.1038/nm1427

    • PubMed
    • Google Scholar

Author details

1. Martina Absinta

   Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Writing—original draft, Writing—review and editing

   Contributed equally with

   Seung-Kwon Ha

   Competing interests

   Dr. Absinta was partially supported by a National Multiple Sclerosis Society (NMSS) fellowship award #FG 2093-A-1 and holds a Marilyn Hilton Award for Innovation in MS research from the Conrad N. Hilton Foundation

   "This ORCID iD identifies the author of this article:" 0000-0003-0276-383X

2. Seung-Kwon Ha

   Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Contributed equally with

   Martina Absinta

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3671-4454

3. Govind Nair

   Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3725-615X

4. Pascal Sati

   Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

5. Nicholas J Luciano

   Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Writing—review and editing

   Competing interests

   No competing interests declared

6. Maryknoll Palisoc

   Hematopathology Section, Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, United States

   Contribution

   Formal analysis, Methodology

   Competing interests

   No competing interests declared

7. Antoine Louveau

   Center for Brain Immunology and Glia, Department of Neuroscience, School of Medicine, University of Virginia, Charlottesville, United States

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

8. Kareem A Zaghloul

   Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8575-3578

9. Stefania Pittaluga

   Hematopathology Section, Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, United States

   Contribution

   Data curation, Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

10. Jonathan Kipnis

    Center for Brain Immunology and Glia, Department of Neuroscience, School of Medicine, University of Virginia, Charlottesville, United States

    Contribution

    Conceptualization, Writing—review and editing

    Competing interests

    No competing interests declared

11. Daniel S Reich

    Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States

    Contribution

    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing

    For correspondence

    reichds@ninds.nih.gov

    Competing interests

    Dr. Reich received research support from collaborations with the Myelin Repair Foundation and Vertex Pharmaceuticals, unrelated to the present study.

    "This ORCID iD identifies the author of this article:" 0000-0002-2628-4334

• 61,023

  views

• 4,483

  downloads

• 423

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.