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Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology.

Frontiers in neuroanatomy

Mori S, Kageyama Y, Hou Z, Aggarwal M, Patel J, Brown T, Miller MI, Wu D, Troncoso JC.
PMID: 28352217
Front Neuroanat. 2017 Mar 14;11:16. doi: 10.3389/fnana.2017.00016. eCollection 2017.

The amygdala has attracted considerable research interest because of its potential involvement in various neuropsychiatric disorders. Recently, attempts have been made using magnetic resonance imaging (MRI) to evaluate the integrity of the axonal connections to and from the amygdala...

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Mori S, Kageyama Y, Hou Z, et al. Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology. Front Neuroanat. 2017;11:16doi: 10.3389/fnana.2017.00016.
Mori, S., Kageyama, Y., Hou, Z., Aggarwal, M., Patel, J., Brown, T., Miller, M. I., Wu, D., & Troncoso, J. C. (2017). Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology. Frontiers in neuroanatomy, 1116. https://doi.org/10.3389/fnana.2017.00016
Mori, Susumu, et al. "Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology." Frontiers in neuroanatomy vol. 11 (2017): 16. doi: https://doi.org/10.3389/fnana.2017.00016
Mori S, Kageyama Y, Hou Z, Aggarwal M, Patel J, Brown T, Miller MI, Wu D, Troncoso JC. Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology. Front Neuroanat. 2017 Mar 14;11:16. doi: 10.3389/fnana.2017.00016. eCollection 2017. PMID: 28352217; PMCID: PMC5348491.
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Cerebral Microvascular Accumulation of Tau Oligomers in Alzheimer's Disease and Related Tauopathies.

Aging and disease

Castillo-Carranza DL, Nilson AN, Van Skike CE, Jahrling JB, Patel K, Garach P, Gerson JE, Sengupta U, Abisambra J, Nelson P, Troncoso J, Ungvari Z, Galvan V, Kayed R.
PMID: 28580182
Aging Dis. 2017 May 02;8(3):257-266. doi: 10.14336/AD.2017.0112. eCollection 2017 May.

The importance of vascular contributions to cognitive impairment and dementia (VCID) associated with Alzheimer's disease (AD) and related neurodegenerative diseases is increasingly recognized, however, the underlying mechanisms remain obscure. There is growing evidence that in addition to Aβ deposition,...

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Castillo-Carranza DL, Nilson AN, Van Skike CE, et al. Cerebral Microvascular Accumulation of Tau Oligomers in Alzheimer's Disease and Related Tauopathies. Aging Dis. 2017;8(3):257-266doi: 10.14336/AD.2017.0112.
Castillo-Carranza, D. L., Nilson, A. N., Van Skike, C. E., Jahrling, J. B., Patel, K., Garach, P., Gerson, J. E., Sengupta, U., Abisambra, J., Nelson, P., Troncoso, J., Ungvari, Z., Galvan, V., & Kayed, R. (2017). Cerebral Microvascular Accumulation of Tau Oligomers in Alzheimer's Disease and Related Tauopathies. Aging and disease, 8(3), 257-266. https://doi.org/10.14336/AD.2017.0112
Castillo-Carranza, Diana L, et al. "Cerebral Microvascular Accumulation of Tau Oligomers in Alzheimer's Disease and Related Tauopathies." Aging and disease vol. 8,3 (2017): 257-266. doi: https://doi.org/10.14336/AD.2017.0112
Castillo-Carranza DL, Nilson AN, Van Skike CE, Jahrling JB, Patel K, Garach P, Gerson JE, Sengupta U, Abisambra J, Nelson P, Troncoso J, Ungvari Z, Galvan V, Kayed R. Cerebral Microvascular Accumulation of Tau Oligomers in Alzheimer's Disease and Related Tauopathies. Aging Dis. 2017 May 02;8(3):257-266. doi: 10.14336/AD.2017.0112. eCollection 2017 May. PMID: 28580182; PMCID: PMC5440106.
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Intraventricular Delivery of siRNA Nanoparticles to the Central Nervous System.

Molecular therapy. Nucleic acids

Shyam R, Ren Y, Lee J, Braunstein KE, Mao HQ, Wong PC.
PMID: 25965552
Mol Ther Nucleic Acids. 2015 May 12;4:e242. doi: 10.1038/mtna.2015.15.

Alzheimer's disease (AD) is a progressive neurodegenerative disease currently lacking effective treatment. Efficient delivery of siRNA via nanoparticles may emerge as a viable therapeutic approach to treat AD and other central nervous system disorders. We report here the use...

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Shyam R, Ren Y, Lee J, et al. Intraventricular Delivery of siRNA Nanoparticles to the Central Nervous System. Mol Ther Nucleic Acids. 2015;4:e242doi: 10.1038/mtna.2015.15.
Shyam, R., Ren, Y., Lee, J., Braunstein, K. E., Mao, H. Q., & Wong, P. C. (2015). Intraventricular Delivery of siRNA Nanoparticles to the Central Nervous System. Molecular therapy. Nucleic acids, 4e242. https://doi.org/10.1038/mtna.2015.15
Shyam, Rishab, et al. "Intraventricular Delivery of siRNA Nanoparticles to the Central Nervous System." Molecular therapy. Nucleic acids vol. 4 (2015): e242. doi: https://doi.org/10.1038/mtna.2015.15
Shyam R, Ren Y, Lee J, Braunstein KE, Mao HQ, Wong PC. Intraventricular Delivery of siRNA Nanoparticles to the Central Nervous System. Mol Ther Nucleic Acids. 2015 May 12;4:e242. doi: 10.1038/mtna.2015.15. PMID: 25965552.
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Alzheimer's disease genetic risk variants beyond .

Alzheimer's & dementia (Amsterdam, Netherlands)

Mez J, Marden JR, Mukherjee S, Walter S, Gibbons LE, Gross AL, Zahodne LB, Gilsanz P, Brewster P, Nho K, Crane PK, Larson EB, Glymour MM.
PMID: 28983503
Alzheimers Dement (Amst). 2017 Aug 14;8:188-195. doi: 10.1016/j.dadm.2017.07.002. eCollection 2017.

INTRODUCTION: We hypothesized that, like apolipoprotein E (METHODS: We used a weighted genetic risk score (GRS) from 21 non-RESULTS: Higher GRS predicted mortality (hazard ratio = 1.05; 95% confidence interval: 1.00-1.10, DISCUSSION: Non-

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Mez J, Marden JR, Mukherjee S, et al. Alzheimer's disease genetic risk variants beyond . Alzheimers Dement (Amst). 2017;8:188-195doi: 10.1016/j.dadm.2017.07.002.
Mez, J., Marden, J. R., Mukherjee, S., Walter, S., Gibbons, L. E., Gross, A. L., Zahodne, L. B., Gilsanz, P., Brewster, P., Nho, K., Crane, P. K., Larson, E. B., & Glymour, M. M. (2017). Alzheimer's disease genetic risk variants beyond . Alzheimer's & dementia (Amsterdam, Netherlands), 8188-195. https://doi.org/10.1016/j.dadm.2017.07.002
Mez, Jesse, et al. "Alzheimer's disease genetic risk variants beyond ." Alzheimer's & dementia (Amsterdam, Netherlands) vol. 8 (2017): 188-195. doi: https://doi.org/10.1016/j.dadm.2017.07.002
Mez J, Marden JR, Mukherjee S, Walter S, Gibbons LE, Gross AL, Zahodne LB, Gilsanz P, Brewster P, Nho K, Crane PK, Larson EB, Glymour MM. Alzheimer's disease genetic risk variants beyond . Alzheimers Dement (Amst). 2017 Aug 14;8:188-195. doi: 10.1016/j.dadm.2017.07.002. eCollection 2017. PMID: 28983503; PMCID: PMC5604953.
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A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium.

Alzheimer's & dementia (Amsterdam, Netherlands)

Gross AL, Hassenstab JJ, Johnson SC, Clark LR, Resnick SM, Kitner-Triolo M, Masters CL, Maruff P, Morris JC, Soldan A, Pettigrew C, Albert MS.
PMID: 28653035
Alzheimers Dement (Amst). 2017 May 30;8:147-155. doi: 10.1016/j.dadm.2017.05.003. eCollection 2017.

INTRODUCTION: We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer's disease and validated the method by examining its relationship with clinical status and cognition.METHODS: Cognitive and clinical data were used from five studies (RESULTS: In...

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Gross AL, Hassenstab JJ, Johnson SC, et al. A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimers Dement (Amst). 2017;8:147-155doi: 10.1016/j.dadm.2017.05.003.
Gross, A. L., Hassenstab, J. J., Johnson, S. C., Clark, L. R., Resnick, S. M., Kitner-Triolo, M., Masters, C. L., Maruff, P., Morris, J. C., Soldan, A., Pettigrew, C., & Albert, M. S. (2017). A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimer's & dementia (Amsterdam, Netherlands), 8147-155. https://doi.org/10.1016/j.dadm.2017.05.003
Gross, Alden L, et al. "A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium." Alzheimer's & dementia (Amsterdam, Netherlands) vol. 8 (2017): 147-155. doi: https://doi.org/10.1016/j.dadm.2017.05.003
Gross AL, Hassenstab JJ, Johnson SC, Clark LR, Resnick SM, Kitner-Triolo M, Masters CL, Maruff P, Morris JC, Soldan A, Pettigrew C, Albert MS. A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimers Dement (Amst). 2017 May 30;8:147-155. doi: 10.1016/j.dadm.2017.05.003. eCollection 2017. PMID: 28653035; PMCID: PMC5476965.
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Fall Risk is Not Black and White.

Journal of health disparities research and practice

Kiely DK, Kim DH, Gross AL, Habtemariam DA, Leveille SG, Li W, Lipsitz LA.
PMID: 26855845
J Health Dispar Res Pract. 2015;8(3):72-84.

OBJECTIVE: To determine whether previously reported racial differences in fall rates between White and Black/African American is explained by differences in health status and neighborhood characteristics.DESIGN: Prospective cohort.SETTING: Community.PARTICIPANTS: The study included 550 White and 116 Black older adults...

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Kiely DK, Kim DH, Gross AL, et al. Fall Risk is Not Black and White. J Health Dispar Res Pract. 2015;8(3):72-84
Kiely, D. K., Kim, D. H., Gross, A. L., Habtemariam, D. A., Leveille, S. G., Li, W., & Lipsitz, L. A. (2015). Fall Risk is Not Black and White. Journal of health disparities research and practice, 8(3), 72-84.
Kiely, Dan K, et al. "Fall Risk is Not Black and White." Journal of health disparities research and practice vol. 8,3 (2015): 72-84.
Kiely DK, Kim DH, Gross AL, Habtemariam DA, Leveille SG, Li W, Lipsitz LA. Fall Risk is Not Black and White. J Health Dispar Res Pract. 2015;8(3):72-84. PMID: 26855845; PMCID: PMC4739813.
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Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing.

Frontiers in bioengineering and biotechnology

Miller MI, Ratnanather JT, Tward DJ, Brown T, Lee DS, Ketcha M, Mori K, Wang MC, Mori S, Albert MS, Younes L.
PMID: 26284236
Front Bioeng Biotechnol. 2015 May 15;3:54. doi: 10.3389/fbioe.2015.00054. eCollection 2015.

This paper examines MRI analysis of neurodegeneration in Alzheimer's Disease (AD) in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into eight subareas. The...

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Miller MI, Ratnanather JT, Tward DJ, et al. Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing. Front Bioeng Biotechnol. 2015;3:54doi: 10.3389/fbioe.2015.00054.
Miller, M. I., Ratnanather, J. T., Tward, D. J., Brown, T., Lee, D. S., Ketcha, M., Mori, K., Wang, M. C., Mori, S., Albert, M. S., Younes, L. (2015). Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing. Frontiers in bioengineering and biotechnology, 354. https://doi.org/10.3389/fbioe.2015.00054
Miller, Michael I, et al. "Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing." Frontiers in bioengineering and biotechnology vol. 3 (2015): 54. doi: https://doi.org/10.3389/fbioe.2015.00054
Miller MI, Ratnanather JT, Tward DJ, Brown T, Lee DS, Ketcha M, Mori K, Wang MC, Mori S, Albert MS, Younes L. Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing. Front Bioeng Biotechnol. 2015 May 15;3:54. doi: 10.3389/fbioe.2015.00054. eCollection 2015. PMID: 26284236; PMCID: PMC4515983.
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Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles.

Frontiers in neuroscience

Tang X, Crocetti D, Kutten K, Ceritoglu C, Albert MS, Mori S, Mostofsky SH, Miller MI.
PMID: 25784852
Front Neurosci. 2015 Mar 03;9:61. doi: 10.3389/fnins.2015.00061. eCollection 2015.

We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain. The pipeline is constructed based on a two-level Bayesian parameter estimation algorithm called multi-atlas likelihood fusion (MALF). In...

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Tang X, Crocetti D, Kutten K, et al. Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles. Front Neurosci. 2015;9:61doi: 10.3389/fnins.2015.00061.
Tang, X., Crocetti, D., Kutten, K., Ceritoglu, C., Albert, M. S., Mori, S., Mostofsky, S. H., & Miller, M. I. (2015). Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles. Frontiers in neuroscience, 961. https://doi.org/10.3389/fnins.2015.00061
Tang, Xiaoying, et al. "Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles." Frontiers in neuroscience vol. 9 (2015): 61. doi: https://doi.org/10.3389/fnins.2015.00061
Tang X, Crocetti D, Kutten K, Ceritoglu C, Albert MS, Mori S, Mostofsky SH, Miller MI. Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles. Front Neurosci. 2015 Mar 03;9:61. doi: 10.3389/fnins.2015.00061. eCollection 2015. PMID: 25784852; PMCID: PMC4347448.
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Computational analysis of LDDMM for brain mapping.

Frontiers in neuroscience

Ceritoglu C, Tang X, Chow M, Hadjiabadi D, Shah D, Brown T, Burhanullah MH, Trinh H, Hsu JT, Ament KA, Crocetti D, Mori S, Mostofsky SH, Yantis S, Miller MI, Ratnanather JT.
PMID: 23986653
Front Neurosci. 2013 Aug 27;7:151. doi: 10.3389/fnins.2013.00151. eCollection 2013.

One goal of computational anatomy (CA) is to develop tools to accurately segment brain structures in healthy and diseased subjects. In this paper, we examine the performance and complexity of such segmentation in the framework of the large deformation...

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Ceritoglu C, Tang X, Chow M, et al. Computational analysis of LDDMM for brain mapping. Front Neurosci. 2013;7:151doi: 10.3389/fnins.2013.00151.
Ceritoglu, C., Tang, X., Chow, M., Hadjiabadi, D., Shah, D., Brown, T., Burhanullah, M. H., Trinh, H., Hsu, J. T., Ament, K. A., Crocetti, D., Mori, S., Mostofsky, S. H., Yantis, S., Miller, M. I., & Ratnanather, J. T. (2013). Computational analysis of LDDMM for brain mapping. Frontiers in neuroscience, 7151. https://doi.org/10.3389/fnins.2013.00151
Ceritoglu, Can, et al. "Computational analysis of LDDMM for brain mapping." Frontiers in neuroscience vol. 7 (2013): 151. doi: https://doi.org/10.3389/fnins.2013.00151
Ceritoglu C, Tang X, Chow M, Hadjiabadi D, Shah D, Brown T, Burhanullah MH, Trinh H, Hsu JT, Ament KA, Crocetti D, Mori S, Mostofsky SH, Yantis S, Miller MI, Ratnanather JT. Computational analysis of LDDMM for brain mapping. Front Neurosci. 2013 Aug 27;7:151. doi: 10.3389/fnins.2013.00151. eCollection 2013. PMID: 23986653; PMCID: PMC3753595.
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Frontotemporal dementia and psychiatry.

International review of psychiatry (Abingdon, England)

Onyike CU, Huey ED.
PMID: 23611342
Int Rev Psychiatry. 2013 Apr;25(2):127-9. doi: 10.3109/09540261.2013.785169.

No abstract available.

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Onyike CU, Huey ED. Frontotemporal dementia and psychiatry. Int Rev Psychiatry. 2013;25(2):127-9doi: 10.3109/09540261.2013.785169.
Onyike, C. U., & Huey, E. D. (2013). Frontotemporal dementia and psychiatry. International review of psychiatry (Abingdon, England), 25(2), 127-9. https://doi.org/10.3109/09540261.2013.785169
Onyike, Chiadi U, and Huey, Edward D. "Frontotemporal dementia and psychiatry." International review of psychiatry (Abingdon, England) vol. 25,2 (2013): 127-9. doi: https://doi.org/10.3109/09540261.2013.785169
Onyike CU, Huey ED. Frontotemporal dementia and psychiatry. Int Rev Psychiatry. 2013 Apr;25(2):127-9. doi: 10.3109/09540261.2013.785169. PMID: 23611342; PMCID: PMC3947598.
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BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES.

The annals of applied statistics

Tang X, Miller MI, Younes L.
PMID: 30271520
Ann Appl Stat. 2017 Sep;11(3):1738-1762. doi: 10.1214/17-AOAS1056.

We consider in this paper a statistical two-phase regression model in which the change point of a disease biomarker is measured relative to another point in time, such as the manifestation of the disease, which is subject to right-censoring...

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Tang X, Miller MI, Younes L. BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES. Ann Appl Stat. 2017;11(3):1738-1762doi: 10.1214/17-AOAS1056.
Tang, X., Miller, M. I., & Younes, L. (2017). BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES. The annals of applied statistics, 11(3), 1738-1762. https://doi.org/10.1214/17-AOAS1056
Tang, Xiaoying, et al. "BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES." The annals of applied statistics vol. 11,3 (2017): 1738-1762. doi: https://doi.org/10.1214/17-AOAS1056
Tang X, Miller MI, Younes L. BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES. Ann Appl Stat. 2017 Sep;11(3):1738-1762. doi: 10.1214/17-AOAS1056. PMID: 30271520; PMCID: PMC6157754.
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'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials.

The journal of prevention of Alzheimer's disease

Leoutsakos JM, Gross AL, Jones RN, Albert MS, Breitner JCS.
PMID: 29034223
J Prev Alzheimers Dis. 2016;3(4):229-235. doi: 10.14283/jpad.2016.120.

BACKGROUND: Alzheimer's disease (AD) prevention research requires methods for measurement of disease progression not yet revealed by symptoms. Preferably, such measurement should encompass multiple disease markers.OBJECTIVES: Evaluate an item response theory (IRT) model-based latent variable Alzheimer Progression Score (APS)...

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Leoutsakos JM, Gross AL, Jones RN, et al. 'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials. J Prev Alzheimers Dis. 2016;3(4):229-235doi: 10.14283/jpad.2016.120.
Leoutsakos, J. M., Gross, A. L., Jones, R. N., Albert, M. S., & Breitner, J. C. S. (2016). 'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials. The journal of prevention of Alzheimer's disease, 3(4), 229-235. https://doi.org/10.14283/jpad.2016.120
Leoutsakos, J-M, et al. "'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials." The journal of prevention of Alzheimer's disease vol. 3,4 (2016): 229-235. doi: https://doi.org/10.14283/jpad.2016.120
Leoutsakos JM, Gross AL, Jones RN, Albert MS, Breitner JCS. 'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials. J Prev Alzheimers Dis. 2016;3(4):229-235. doi: 10.14283/jpad.2016.120. PMID: 29034223; PMCID: PMC5639716.
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Showing 1 to 12 of 134 entries