PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
 
Acta Neuropathol. Mar 2011; 121(3): 327–335.
Published online Dec 7, 2010. doi:  10.1007/s00401-010-0787-6
PMCID: PMC3038220
In vivo multiphoton imaging reveals gradual growth of newborn amyloid plaques over weeks
Steffen Burgold,1 Tobias Bittner,1 Mario M. Dorostkar,1 Daniel Kieser,2 Martin Fuhrmann,1 Gerda Mitteregger,1 Hans Kretzschmar,1 Boris Schmidt,2 and Jochen Hermscorresponding author1
1Center of Neuropathology and Prion Research, Ludwig Maximilians Universität, Feodor-Lynen-Str. 23, 81377 Munich, Germany
2Clemens Schoepf Institute for Organic Chemistry and Biochemistry, Technical University, 64287 Darmstadt, Germany
Jochen Herms, jochen.herms/at/med.uni-muenchen.de.
corresponding authorCorresponding author.
Received October 1, 2010; Revised November 25, 2010; Accepted November 27, 2010.
The kinetics of amyloid plaque formation and growth as one of the characteristic hallmarks of Alzheimer’s disease (AD) are fundamental issues in AD research. Especially the question how fast amyloid plaques grow to their final size after they are born remains controversial. By long-term two-photon in vivo imaging we monitored individual methoxy-X04-stained amyloid plaques over 6 weeks in 12 and 18 months old Tg2576 mice. We found that in 12 months old mice, newly appearing amyloid plaques were initially small in volume and subsequently grew over time. The growth rate of plaques was inversely proportional to their volume; thus amyloid plaques that were already present at the first imaging time point grew over time but slower compared to new plaques. Additionally, we analyzed 18 months old Tg2576 mice in which we neither found newly appearing plaques nor a significant growth of pre-existing plaques over 6 weeks of imaging. In conclusion, newly appearing amyloid plaques are initially small in size but grow over time until plaque growth can not be detected anymore in aged mice. These results suggest that drugs that target plaque formation should be most effective early in the disease, when plaques are growing.
Electronic supplementary material
The online version of this article (doi:10.1007/s00401-010-0787-6) contains supplementary material, which is available to authorized users.
Keywords: Alzheimer’s disease, Amyloid plaque, Aβ, plaque growth, Tg2576, Two-photon, In vivo, Imaging
Amyloid plaques represent one of the major hallmarks of Alzheimer’s disease (AD) pathology. They are comprised of fibrillar aggregates of the amyloid-β-peptide which has been shown to have synaptotoxic effects [10, 17, 18, 23]. In AD patients as well as in animal models synapse loss is most prominent in close proximity to amyloid plaque deposits which indicates a link between amyloid plaques and synaptotoxicity [7, 14, 15, 1921]. Therefore, elucidating the process of amyloid plaque formation and growth may reveal important targets for therapeutic interventions to stop the progression of synapse loss and consequently cognitive decline in AD.
In vitro studies of plaque formation established a model in which a seed of fibrillar Aβ is formed first and plaques grow subsequently around these seeds in a time- and concentration-dependent manner [4, 11]. These findings were corroborated by in vivo imaging studies of AD transgenic (APP/PS1) mice, which reported a change in size of a subset of plaques [2] or a gradual growth of almost all plaques, which was faster in smaller plaques and younger animals [24]. These findings, however, are contrasted by different studies, which reported that Aβ plaques appeared rapidly in both APP/PS1 and Tg2576 transgenic mice [16] and that these were relatively stable over time in Tg2576 transgenic mice [3]. The apparent discrepancies of the in vivo studies may be attributed to a different preparation of the cranial window (e.g., thinned skull vs. open skull preparations), the age of the mice, or different disease models (e.g., APP/PS1 or Tg2576). In order to reconcile these findings, we studied the appearance of Aβ plaques in detail. We followed plaque formation in 12 and 18 months old Tg2576 mice by measuring the volume, as well as area, over a period of 6 weeks. While we used an open skull preparation, we started our imaging protocol 3 weeks after surgery, so that possible artifacts from inflammatory reactions [8] were minimized.
Using this approach, we found that plaques appeared and increased in volume in 12 months old, but not in 18 months old mice. Nascent plaques were initially small in volume and grew over time. Pre-existing plaques, in contrast, had a larger volume and grew slower compared to newly formed ones. These findings demonstrate that Aβ plaques grow in a size-dependent manner in young (12 months) mice, while no growth was observed in older (18 months) mice.
Transgenic mice
Heterozygous Tg2576 [9] mice (B6;SJL-Tg(APPSWE)2576Kha from Taconic, Cologne, Germany) were crossed with heterozygous YFP-H [5] mice (B6.Cg-Tg(Thy1-YFPH)2Jrs/J) from The Jackson Laboratory, Bar Harbor, USA) expressing yellow fluorescent protein (YFP) in a subset of cortical neurons. YFP-labeled neurons served as a counterstaining to find the same imaging positions over and over again in subsequent time points. Mice were of both sexes and were group housed under pathogen-free conditions until surgery, after which they were singly housed. All procedures were performed in accordance with an animal protocol approved by the University of Munich and the Government of Upper Bavaria (55.2-1.54-2531-110-06).
Open-skull surgery
A cranial window over the right cortical hemisphere was surgically implanted as previously described [1, 6, 8]. The mice were anesthetized with an intraperitoneal injection of ketamine/xylazine (0.13/0.01 mg/g body weight). Additionally, dexamethasone (0.02 ml at 4 mg/ml) was intraperitoneally administered immediately before surgery (Holtmaat et al. 2005). A circular piece of the skull (4 mm in diameter) over the right somatosensory cortex (centered over the parietal bone, approx. 5.5 mm caudal from the bregma and 5.5 mm lateral of the midline) was removed using a dental drill (Schick-Technikmaster C1; Pluradent; Offenbach, Germany). Immediately, a round coverslip (5 mm diameter) was glued to the skull using dental acrylic (Cyano-Veneer fast; Heinrich Schein Dental Depot, Munich, Germany) to close the craniotomy. A small metal bar, containing a hole for a screw, was glued next to the coverslip to allow repositioning of the mouse during subsequent imaging sessions. After surgery, mice received a subcutaneous analgesic dose of carprophen (Rimadyl; Pfizer, New York, USA) for 3 days (5 mg/kg). Imaging began following a 21 day rest period after surgery.
Long-term two-photon in vivo imaging
Long-term two-photon imaging was performed as previously described [1, 6]. Less than 50 mW laser power was delivered to the tissue to avoid laser-induced phototoxicity. For amyloid plaque staining, methoxy-X04 [13] was intraperitoneally injected 24 h before every imaging session. Initially, we administered doses of 2.4 mg/kg. However, in an attempt to reduce methoxy-X04 usage, we changed the dosing regimen to an initial loading dose of 2.0 mg/kg before the first imaging session and subsequent weekly maintenance doses of 0.4 mg/kg, which did not affect the signal-to-noise ratio (data not shown). Furthermore, we found no significant difference in plaque growth between these two dosing regimens (Supplementary Fig. S1a), therefore we pooled the data for all further analyses. To determine whether repeated administration of methoxy-X04 increased the apparent volume of plaques by increasing the brightness, we correlated plaque volumes with the mean intensity of the fluorescence values of all voxels in a plaque (Supplementary Fig. S1b). The correlation between plaque volume and intensity was weak (R2 = 0.25) compared to data obtained by imaging fluorescent beads with varying laser intensities to simulate increasing brightness (R2 = 0.71; data not shown). Considering that no plaque growth was observed in older animals despite the same dosing scheme and that comparably little plaque growth was observed with daily administration of methoxy-X04 (Supplementary Fig. S2), changes in plaque volumes cannot be attributed to increased brightness due to methoxy-X04 accumulation.
YFP and methoxy-X04 were excited by a Ti:Sa laser (MaiTai, Spectra-Physics, Darmstadt, Germany) at 880 and 750 nm and the emission was collected from 527 to 582 nm and 460 to 500 nm, respectively (LSM 5MP, Zeiss, Jena, Germany). A Zeiss 20× water-immersion objective (1.0 NA) was used to acquire image stacks of 425 × 425 × 300 μm3 with 3 μm z-resolution and 1,024 × 1,024 pixels per image frame (0.41 μm/pixel). In subsequent imaging sessions, previously imaged volumes were identified by eye, based on the positions of blood vessels, neuronal cell bodies and processes, as well as plaques. This allowed the precise alignment of the same imaging volume over a period of 6 weeks. The laser intensity was adjusted to keep the emitted YFP fluorescence stable.
Image processing and data analysis
The 3D images were deconvolved (AutoDeblur, Version x2.0.1, Media Cybernetics, Bethesda, USA) and contrast-normalized (i.e., based on the average and standard deviation of intensities of 3D stacks; Imaris 6.2.1, Bitplane, Zurich, Switzerland). For 3D analysis, we used surface rendering by Imaris software which also calculated the volume of individual plaques over time period. The 2D analysis was performed in maximum intensity projections applying a threshold of mean intensity + twice standard deviation of a representative background region. The volume growth of individual plaques was quantified as the slope of a linear fit of the volumes measured at each time point. We used repeated measures ANOVA and Student’s t-test to test significance. All data are presented as mean ± SD, and 95% confidence intervals (95% CI) are given where appropriate.
We imaged 83 individual amyloid plaques in 12 months old Tg2576 mice [9] (n = 8) for up to 6 weeks (Fig. 1a). Volumes of individual plaques were three-dimensionally (3D) surface-rendered, quantified, and tracked over time (Fig. 1b). To compare the growth of plaques of various sizes, we normalized the volume of individual plaques to their volume at the first imaging session (week 0). In total, we detected the appearance of 25 new plaques during the imaging period of 6 weeks. Initially, these newborn plaques had an average volume of 255 ± 231 μm3 (95% CI, 159–350 μm3; Fig. 2) and exhibited a significant volume increase of 2,015 ± 1,783% over 6 weeks based on a linear regression (Fig. 3a–c; P < 0.001, R2 = 0.97). The initial area of newborn plaques, as determined from the maximum intensity projection, was 33.8 ± 21.6 μm2 (95% CI, 24.5–43.2 μm2) and they exhibited a significant area increase of 591 ± 409% over 6 weeks based on a linear regression (Fig. 3d; P < 0.001, R2 = 0.95). Plaques that were not observed in their nascent stage, so called pre-existing plaques (n = 58) had an initial average volume of 7,575 ± 15,599 μm3 (95% CI, 3,473–11,676 μm3; Fig. 2) and an initial average area, as determined from the maximum intensity projection, of 141.0 ± 262.1 μm2 (95% CI, 73.3–208.7 μm2). Both volume as well as area was significantly higher compared to newborn plaques (P < 0.001). These pre-existing plaques exhibited a significant linear volume increase of 426 ± 313% over 6 weeks (Fig. 4a–c, P < 0.001, R2 = 0.99), whereas the area increased by 282 ± 123% over 6 weeks based on a linear regression (Fig. 4d; P < 0.001, R2 = 0.97). Collectively, all amyloid plaques analyzed in 12 months old Tg2576 mice significantly gained volume and area over 6 weeks (P < 0.001). In contrast, we neither detected newly appearing plaques, nor a significant increase in plaque volume in 18 months old Tg2576 mice over 6 weeks (Fig. 5; n = 126 plaques in three mice). At this age, amyloid plaques had an average volume of 14,632 ± 27,811 μm3 (95% CI, 9,729–19,536 μm3; Fig. 2), which is significantly higher than at 12 months (Fig. 2, P < 0.001). We also determined the sphericity of the larger, pre-existing plaques, which is defined as the ratio of the surface area of a sphere which has the same volume as the given plaque to the surface area of the plaque [22]. On average, the sphericity of n = 101 plaques was 0.86 ± 0.07 (95% CI, 0.84–0.87), which differed significantly from 1 (i.e., a perfect sphere; Wilcoxon signed rank test, P < 0.0001). Finally, we quantified the growth of individual plaques as the slope of a linear fit of the normalized volumes measured at each time point and plotted these against the initial volumes of each respective plaque (Fig. 6). This analysis shows a slight overlap in volumes of newborn and pre-existing plaques (Fig. 6a). This is most likely due to the sampling rate of plaque volumes (i.e., weekly), so that plaques labeled as “newborn” may have existed for up to a week before we detected them for the first time. More importantly, however, we found that in young (12 months) mice, plaque growth is directly related to the volume of a plaque (Fig. 6a), whereas most plaques in older (18 months) mice show very little, if any, growth (Fig. 6b).
Fig. 1
Fig. 1
Long-term two-photon in vivo imaging of amyloid plaques. a Schematic of a cranial window implanted over the somatosensory cortex of a Tg2576 mouse that was crossed with YFP-H. A volume rendered z-stack with perspective view (45°) shows amyloid (more ...)
Fig. 2
Fig. 2
Distribution of amyloid plaque volumes. Distribution of amyloid plaque volumes between individual newborn (n = 25) and pre-existing plaques (n = 58) in 12 months old Tg2576 and pre-existing plaques (n = 128) (more ...)
Fig. 3
Fig. 3
Growth of newborn amyloid plaques in 12 months old Tg2576. a Maximum intensity projections of a time series of 3D images acquired with two-photon in vivo imaging in 12 months old Tg2576 mice. A newborn amyloid plaque (stained with methoxy-X04) (more ...)
Fig. 4
Fig. 4
Growth of pre-existing amyloid plaques in 12 months old Tg2576. a Maximum intensity projections of a time series of 3D images acquired with two-photon in vivo imaging in 12 months old Tg2576 mice. A pre-existing amyloid plaque (stained (more ...)
Fig. 5
Fig. 5
Growth of pre-existing amyloid plaques in 18 months old Tg2576. a Maximum intensity projections of a time series of 3D images acquired with two-photon in vivo imaging in 18 months old Tg2576 mice. A pre-existing amyloid plaque (stained (more ...)
Fig. 6
Fig. 6
Relationship between growth and initial volume of amyloid plaques. The growth of amyloid plaques is quantified as the slope of a linear fit of the normalized volumes measured at each time point and is shown as a function of the initial volume of plaques. (more ...)
We monitored the appearance and growth of Aβ plaques in Tg2576 mice by in vivo two-photon microscopy of animals pretreated with methoxy-X04, which stains Aβ plaques. As a model, we used Tg2576 mice, which overexpress a human APP transgene containing the Swedish FAD mutation (K670N/M671L), and display the slowest amyloid pathology [9] of all the models analyzed by Meyer-Luehmann et al. [16]. We reasoned that if we were able to detect amyloid plaque growth in this model, then it should also be detectable in other mouse models with a faster amyloid pathology.
In summary, we showed that in the early stages of amyloid pathology in Tg2576 mice, newborn plaques are initially small in size and grow over time. These findings are in contrast to the previous study by Meyer-Luehmann et al. [16] which found that plaques appeared very rapidly (within 24 h) and did not change significantly in size thereafter. One possible reason for the differing results might be the fact that we primarily quantified volume, rather than area. However, even when we quantified plaque size as an area, that area steadily increased over 6 weeks (Figs. 3d, d,4d).4d). Thus, quantification of the plaques in three dimensions does not account for the observed difference. Another possibility is that open-skull surgery induces local inflammation and gliosis in the first weeks after surgery [8], which may affect plaque growth [24]. Therefore, in contrast to Meyer-Luehmann et al. [16], we waited for 3 weeks before imaging, so that possible inflammatory responses could abate. Yet even when we started daily imaging immediately after cranial window surgery, we were able to measure plaque growth. Initial plaque volumes were 92.1 ± 64.5 μm3 (95% CI, 60.0–124 μm3; n = 18). However, a significant increase in plaque volume was only detected if we monitored plaque sizes for more than 16 days (Supplementary Fig. S2). Thus, delayed imaging 3 weeks after surgery does not account for the observed differences, either. We identified, however, two factors which determined if plaque growth can be observed in Tg2576 mice; first, and most importantly, we found that plaque growth can only be detected after a sufficiently long observation period. We monitored plaques for six consecutive weeks and detected that a statistically significant change in plaque volume of newborn plaques was achieved not earlier than 2 weeks after their first appearance (Fig. 3c), whereas a statistically significant change in plaque volume of pre-existing plaques was achieved not earlier than 4 weeks after the initial measurement (Fig. 4c). Second, we also found that the age of the observed animals plays an important role; we detected plaque growth in 12 months old mice, whereas 18 months old mice showed no significant overall growth of plaques (Figs. 5c, c,6),6), which was shown before by Christie et al. [3]. Glial interaction with amyloid deposits has previously been suggested as a possible explanation for this observation in old mice [3]. However, we would further like to propose the possibility that the high number of existing amyloid plaques at this age and therefore the large total surface area where newly formed Aβ fibrils can attach to existing plaques could lead to a decelerated growth of each individual plaque up to a degree that it is not detectable by two-photon in vivo imaging anymore. It is furthermore interesting to note that plaque size varied widely in 18 months old animals (Fig. 2); yet we observed no newborn plaques at that age (Fig. 6). Individual plaques, however, seemed both to shrink and grow between measurements (Fig. 5). While this suggests the exciting possibility that plaques might be in a dynamic equilibrium, increasing measurement errors with increasing plaque size (note the heteroscedasticity in Figs. 3c, c,4c)4c) preclude us from making a firm conclusion. Thus, our data show that both the appropriate age and an appropriate observation period are required in order to detect plaque growth. Furthermore, our findings corroborate results which showed plaque growth in different double-transgenic AD mouse models [2, 24].
In conclusion, we show that amyloid plaques do grow in 12 months old Tg2576 mice when amyloid pathology is in the early stages [9]. Newborn amyloid plaques are initially small in size and grow over the following weeks. After the initial growth period, plaques continue to grow, albeit more slowly, until plaque growth is not detectable anymore in aged mice. These findings have important implications for AD diagnosis and therapy. A recent study [12], for instance, showed that in patients with mild cognitive impairment (MCI), amyloid plaque load, as measured by 11C-Pittsburgh compound B (PIB) retention in positron emission tomography, increased over 5 years, while the regional cerebral metabolic rate of glucose decreased. However, cognitive function remained stable in these patients. Patients with AD, in contrast, had higher PIB retention than patients with MCI, which did not increase further over the observation period, and showed a decline in the regional cerebral metabolic rate of glucose as well as in cognitive function. In combination with our results, these data suggest that plaque formation occurs early in the course of the disease, but before a loss of cognitive function becomes apparent. Therefore, drugs that target plaque formation should be most effective early in the disease, when plaques are growing. These results also suggest that a different mechanism may be responsible for the cognitive decline in patients with manifest AD. Thus, an effort has to be made to find the mechanism of cognitive decline in the late disease stages in order to tailor effective therapeutic strategies.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Fig. S1 Methoxy-X04 dosing has no effect on apparent plaque growth. (a) The maintenance dose of methoxy-X04 has no effect on the relative plaque growth. The growth of amyloid plaques is quantified as the slope of a linear fit of the normalized volumes measured over 6 weeks. Data shown represent pre-existing plaques in 12 months old animals. The red lines show mean and standard deviation; n = 31 (0.4 mg/kg) and 23 (2.4 mg/kg); P > 0.2 (Mann–Whitney test). (b) The log-transformed volumes of plaques are expressed as a function of the mean intensity of pixel values of the respective plaque after contrast normalization (black circles). The data were fit with a linear regression (red line; k = 0.0165 ± 0.0014, R
2
 = 0.25) with the result that plaque volume and pixel intensity are weakly correlated.
Fig. S2 Growth of newborn amyloid plaques in 12 months old Tg2576 imaged in daily intervals in the first week after surgery. The diagram shows normalized volumes of 10 individual plaques (grey lines) based on the volume at first appearance. Measurements started immediately after cranial window surgery. Day 0 is set as the first imaging time-point. Average plaque volumes (red triangles), and linear regression of average plaque volume (red line) over 6 weeks are displayed. Error bars show standard deviation; ** P < 0.01, *** P < 0.001;
Acknowledgments
This work was supported by grants from the Deutsche Forschungsgemeinschaft (SFB 596, A13), the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, 01GZ0713, 13N9268), the German Federal Ministry of Economics and Technology (Bundesministerium für Wirtschaft und Technologie, 16IN0675) and the European Union (Neuro.GSK3, FP-7-223276). Furthermore, the authors would like to thank Sonja Steinbach for her excellent technical assistance and Patrizia Bonert for her invaluable assistance in animal care.
Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
1. Bittner T, Fuhrmann M, Burgold S, et al. gamma-Secretase inhibition reduces spine density in vivo via an amyloid precursor protein-dependent pathway. J Neurosci. 2009;29:10405–10409. doi: 10.1523/JNEUROSCI.2288-09.2009. [PubMed] [Cross Ref]
2. Bolmont T, Haiss F, Eicke D, et al. Dynamics of the microglial/amyloid interaction indicate a role in plaque maintenance. J Neurosci. 2008;28:4283–4292. doi: 10.1523/JNEUROSCI.4814-07.2008. [PubMed] [Cross Ref]
3. Christie RH, Bacskai BJ, Zipfel WR, et al. Growth arrest of individual senile plaques in a model of Alzheimer’s disease observed by in vivo multiphoton microscopy. J Neurosci. 2001;21:858–864. [PubMed]
4. Esler WP, Stimson ER, Ghilardi JR, et al. In vitro growth of Alzheimer’s disease beta-amyloid plaques displays first-order kinetics. Biochemistry. 1996;35:749–757. doi: 10.1021/bi951685w. [PubMed] [Cross Ref]
5. Feng G, Mellor RH, Bernstein M, et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron. 2000;28:41–51. doi: 10.1016/S0896-6273(00)00084-2. [PubMed] [Cross Ref]
6. Fuhrmann M, Bittner T, Jung CKE, et al. Microglial CX3CR1 knockout prevents neuron loss in a mouse model of Alzheimer’s disease. Nat Neurosci. 2010;13:411–413. doi: 10.1038/nn.2511. [PubMed] [Cross Ref]
7. Grutzendler J, Helmin K, Tsai J, Gan WB. Various dendritic abnormalities are associated with fibrillar amyloid deposits in Alzheimer’s disease. Ann NY Acad Sci. 2007;1097:30–39. doi: 10.1196/annals.1379.003. [PubMed] [Cross Ref]
8. Holtmaat A, Bonhoeffer T, Chow DK, et al. Long-term, high-resolution imaging in the mouse neocortex through a chronic cranial window. Nat Protocols. 2009;4:1128–1144. doi: 10.1038/nprot.2009.89. [PMC free article] [PubMed] [Cross Ref]
9. Hsiao K, Chapman P, Nilsen S, et al. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science. 1996;274:99–102. doi: 10.1126/science.274.5284.99. [PubMed] [Cross Ref]
10. Hsieh H, Boehm J, Sato C, et al. AMPAR removal underlies Abeta-induced synaptic depression and dendritic spine loss. Neuron. 2006;52:831–843. doi: 10.1016/j.neuron.2006.10.035. [PMC free article] [PubMed] [Cross Ref]
11. Jarrett JT, Lansbury PT. Seeding one-dimensional crystallization of amyloid––a pathogenic mechanism in Alzheimer’s disease and scrapie. Cell. 1993;73:1055–1058. doi: 10.1016/0092-8674(93)90635-4. [PubMed] [Cross Ref]
12. Kadir A, Almkvist O, Forsberg A et al (2010) Dynamic changes in PET amyloid and FDG imaging at different stages of Alzheimer’s disease. Neurobiol Aging. doi:10.1016/j.neurobiolaging.2010.06.015. [PubMed]
13. Klunk WE, Bacskai BJ, Mathis CA, et al. Imaging Abeta plaques in living transgenic mice with multiphoton microscopy and methoxy-X04, a systemically administered Congo red derivative. J Neuropathol Exp Neurol. 2002;61:797–805. [PubMed]
14. Knafo S, Alonso-Nanclares L, Gonzalez-Soriano J, et al. Widespread changes in dendritic spines in a model of Alzheimer’s disease. Cereb Cortex. 2009;19:586–592. doi: 10.1093/cercor/bhn111. [PubMed] [Cross Ref]
15. Koffie RM, Meyer-Luehmann M, Hashimoto T, et al. Oligomeric amyloid beta associates with postsynaptic densities and correlates with excitatory synapse loss near senile plaques. Proc Natl Acad Sci USA. 2009;106:4012–4017. doi: 10.1073/pnas.0811698106. [PubMed] [Cross Ref]
16. Meyer-Luehmann M, Spires-Jones TL, Prada C, et al. Rapid appearance and local toxicity of amyloid-beta plaques in a mouse model of Alzheimer’s disease. Nature. 2008;451:720–724. doi: 10.1038/nature06616. [PMC free article] [PubMed] [Cross Ref]
17. Shankar GM, Li SM, Mehta TH, et al. Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory. Nat Med. 2008;14:837–842. doi: 10.1038/nm1782. [PMC free article] [PubMed] [Cross Ref]
18. Snyder EM, Nong Y, Almeida CG, et al. Regulation of NMDA receptor trafficking by amyloid-beta. Nat Neurosci. 2005;8:1051–1058. doi: 10.1038/nn1503. [PubMed] [Cross Ref]
19. Spires TL, Meyer-Luehmann M, Stern EA, et al. Dendritic spine abnormalities in amyloid precursor protein transgenic mice demonstrated by gene transfer and intravital multiphoton microscopy. J Neurosci. 2005;25:7278–7287. doi: 10.1523/JNEUROSCI.1879-05.2005. [PMC free article] [PubMed] [Cross Ref]
20. Spires-Jones TL, Meyer-Luehmann M, Osetek JD, et al. Impaired spine stability underlies plaque-related spine loss in an Alzheimer’s disease mouse model. Am J Pathol. 2007;171:1304–1311. doi: 10.2353/ajpath.2007.070055. [PubMed] [Cross Ref]
21. Tsai J, Grutzendler J, Duff K, Gan WB. Fibrillar amyloid deposition leads to local synaptic abnormalities and breakage of neuronal branches. Nat Neurosci. 2004;7:1181–1183. doi: 10.1038/nn1335. [PubMed] [Cross Ref]
22. Wadell H. Volume, shape, and roundness of quartz particles. J Geol. 1935;43:250–280. doi: 10.1086/624298. [Cross Ref]
23. Wei W, Nguyen LN, Kessels HW, et al. Amyloid beta from axons and dendrites reduces local spine number and plasticity. Nat Neurosci. 2010;13:190–196. doi: 10.1038/nn.2476. [PMC free article] [PubMed] [Cross Ref]
24. Yan P, Bero AW, Cirrito JR, et al. Characterizing the appearance and growth of amyloid plaques in APP/PS1 mice. J Neurosci. 2009;29:10706–10714. doi: 10.1523/JNEUROSCI.2637-09.2009. [PMC free article] [PubMed] [Cross Ref]
Articles from Springer Open Choice are provided here courtesy of
Springer