Journal articles on the topic 'Neuropathology'

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1

Mattsson-Carlgren, Niklas, Lea T. Grinberg, Adam Boxer, Rik Ossenkoppele, Magnus Jonsson, William Seeley, Alexander Ehrenberg, et al. "Cerebrospinal Fluid Biomarkers in Autopsy-Confirmed Alzheimer Disease and Frontotemporal Lobar Degeneration." Neurology 98, no. 11 (February 16, 2022): e1137-e1150. http://dx.doi.org/10.1212/wnl.0000000000200040.

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Background and ObjectivesTo determine how fully automated Elecsys CSF immunoassays for β-amyloid (Aβ) and tau biomarkers and an ultrasensitive Simoa assay for neurofilament light chain (NFL) correlate with neuropathologic changes of Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD).MethodsWe studied 101 patients with antemortem CSF and neuropathology data. CSF samples were collected a mean of 2.9 years before death (range 0.2–7.5 years). CSF was analyzed for Aβ40, Aβ42, total tau (T-tau), tau phosphorylated at amino acid residue 181 (P-tau), P-tau/Aβ42 and Aβ42/Aβ40 ratios, and NFL. Neuropathology measures included Thal phases, Braak stages, Consortium to Establish a Registry for Alzheimer's Disease (CERAD) scores, AD neuropathologic change (ADNC), and primary and contributory pathologic diagnoses. Associations between CSF biomarkers and neuropathologic features were tested in regression models adjusted for age, sex, and time from sampling to death.ResultsCSF biomarkers were associated with neuropathologic measures of Aβ (Thal, CERAD score), tau (Braak stage), and overall ADNC. The CSF P-tau/Aβ42 and Aβ42/Aβ40 ratios had high sensitivity, specificity, and overall diagnostic performance for intermediate-high ADNC (area under the curve range 0.95–0.96). Distinct biomarker patterns were seen in different FTLD subtypes, with increased NFL and reduced P-tau/T-tau in FTLD–TAR DNA-binding protein 43 and reduced T-tau in progressive supranuclear palsy compared to other FTLD variants.DiscussionCSF biomarkers, including P-tau, T-tau, Aβ42, Aβ40, and NFL, support in vivo identification of AD neuropathology and correlate with FTLD neuropathology.Classification of EvidenceThis study provides Class II evidence that distinct CSF biomarker patterns, including for P-tau, T-tau, Aβ42, Aβ40, and NFL, are associated with AD and FTLD neuropathology.
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2

Wallace, Lindsay M. K., Olga Theou, Sultan Darvesh, David A. Bennett, Aron S. Buchman, Melissa K. Andrew, Susan A. Kirkland, John D. Fisk, and Kenneth Rockwood. "Neuropathologic burden and the degree of frailty in relation to global cognition and dementia." Neurology 95, no. 24 (September 28, 2020): e3269-e3279. http://dx.doi.org/10.1212/wnl.0000000000010944.

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ObjectiveTo test the hypothesis that degree of frailty and neuropathologic burden independently contribute to global cognition and odds of dementia.MethodsThis was a secondary analysis of a prospective cohort study of older adults living in Illinois. Participants underwent an annual neuropsychological and clinical evaluation. We included 625 participants (mean age 89.7 ± 6.1 years; 67.5% female) who died and underwent autopsy. We quantified neuropathology using an index measure of 10 neuropathologic features: β-amyloid deposition, hippocampal sclerosis, Lewy bodies, tangle density, TDP-43, cerebral amyloid angiopathy, arteriolosclerosis, atherosclerosis, and gross and chronic cerebral infarcts. Clinical consensus determined dementia status, which we coded as no cognitive impairment, mild cognitive impairment, or dementia. A battery of 19 tests spanning multiple domains quantified global cognition. We operationalized frailty using a 41-item frailty index. We employed regression analyses to model relationships between neuropathology, frailty, and dementia.ResultsBoth frailty and a neuropathology index were independently associated with global cognition and dementia status. These results held after controlling for traditional pathologic measures in a sample of participants with Alzheimer clinical syndrome. Frailty improved the fit of the model for dementia status (χ2[2] 72.64; p < 0.0001) and explained an additional 11%–12% of the variance in the outcomes.ConclusionDementia is a multiply determined condition, to which both general health, as captured by frailty, and neuropathology significantly contribute. This integrative view of dementia and health has implications for prevention and therapy; specifically, future research should evaluate frailty as a means of dementia risk reduction.
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3

Blackburn, Jessica, Diana L. Thomas, Anna Hughes, and Christopher R. Pierson. "Neuropathology of Septo-optic Dysplasia: A Report of 4 Autopsy Cases." Journal of Child Neurology 36, no. 2 (September 14, 2020): 105–15. http://dx.doi.org/10.1177/0883073820954071.

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Septo-optic dysplasia (SOD) is defined by the presence of 2 or more features in a diagnostic triad: (1) optic nerve hypoplasia, (2) pituitary dysfunction, and (3) midline forebrain anomalies. SOD arises due to diverse pathogenetic mechanisms including acquired and genetic factors, and it shows considerable clinical and phenotypic variability. Our knowledge of SOD is incomplete in part because of a paucity of published neuropathology data, so we reviewed the autopsy neuropathology of 4 SOD patients. All patients met SOD criteria according to the triad. Additional neuropathologic findings included malformations involving non-forebrain structures and possible secondary phenomena. Autopsies demonstrate that SOD patients often have additional neuropathologic findings beyond the triad and we feel that use of the term SOD-complex appropriately underscores this diversity and its likely clinical impact. This study suggests that autopsies enhance our understanding of SOD and may be an asset in performing needed clinical and phenotypic correlation studies.
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4

Saito, Yuko, and Shigeo Murayama. "Neuropathology." Rinsho Shinkeigaku 51, no. 11 (2011): 1168–71. http://dx.doi.org/10.5692/clinicalneurol.51.1168.

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5

Squier, M. V. "Neuropathology." AVMA Medical & Legal Journal 2, no. 2 (March 1996): 37–42. http://dx.doi.org/10.1177/135626229600200202.

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6

Hart, Michael N. "Neuropathology." Journal of Neuropathology and Experimental Neurology 64, no. 10 (October 2005): 923. http://dx.doi.org/10.1097/01.jnen.0000182984.87106.1f.

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7

Tremblay, G. F. "Neuropathology." Neurology 39, no. 2 (February 1, 1989): 313. http://dx.doi.org/10.1212/wnl.39.2.313.

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8

Almira-Suarez, Maria Isabel, and Maria Beatriz Lopes. "Neuropathology." American Journal of Surgical Pathology 37, no. 11 (November 2013): 1768. http://dx.doi.org/10.1097/pas.0000000000000084.

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9

Pinckard, J. Keith. "Neuropathology." Academic Forensic Pathology 2, no. 1 (March 2012): vi—vii. http://dx.doi.org/10.1177/192536211200200101.

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10

Renshaw, Andrew. "Neuropathology." Advances in Anatomic Pathology 13, no. 1 (January 2006): 62. http://dx.doi.org/10.1097/01.pap.0000201830.69849.b9.

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11

Mischel, Paul S., and Harry V. Vinters. "Neuropathology." Neurosurgery Clinics of North America 6, no. 3 (July 1995): 565–80. http://dx.doi.org/10.1016/s1042-3680(18)30450-9.

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12

Tihan, Tarik. "Neuropathology." Surgical Pathology Clinics 8, no. 1 (March 2015): i. http://dx.doi.org/10.1016/s1875-9181(15)00004-5.

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13

Ng, Thomas H. K. "Neuropathology." Pathology 31, no. 4 (1999): 442. http://dx.doi.org/10.1016/s0031-3025(16)34759-6.

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14

Dayan, A. "Neuropathology." Journal of Clinical Pathology 42, no. 3 (March 1, 1989): 334. http://dx.doi.org/10.1136/jcp.42.3.334-b.

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15

Timperley, W. R. "Neuropathology." Journal of Clinical Pathology 53, no. 4 (April 1, 2000): 255–65. http://dx.doi.org/10.1136/jcp.53.4.255.

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16

Reifenberger, G., and J. Bell. "Neuropathology." Journal of Neurovirology 8, no. 3 (January 2002): 26–27. http://dx.doi.org/10.1080/13550280290049886.

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17

Fazakerley, J., and E. Neuen-Jacob. "Neuropathology." Journal of Neurovirology 8, no. 3 (January 2002): 71–78. http://dx.doi.org/10.1080/13550280290050064.

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18

ALVORD, ELLSWORTH C., and JOSEPH R. SIEBERT. "Neuropathology." Journal of Neuropathology and Experimental Neurology 56, no. 12 (December 1997): 1373–74. http://dx.doi.org/10.1097/00005072-199712000-00014.

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19

Garcia, Julio. "Neuropathology." Journal of Neuropathology and Experimental Neurology 57, no. 2 (February 1998): 203. http://dx.doi.org/10.1097/00005072-199802000-00011.

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20

Lowe, J. "Neuropathology." Journal of Pathology 168, no. 2 (October 1992): 249–53. http://dx.doi.org/10.1002/path.1711680215.

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21

Swerdlow, Neal R., and Anne B. Young. "Neuropathology in Tourette Syndrome." CNS Spectrums 4, no. 3 (March 1999): 65–74. http://dx.doi.org/10.1017/s1092852900000833.

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ABSTRACTThe unique clinical presentation of Tourette syndrome (TS) and its symptomatic response to dopamine antagonists are widely cited as evidence for the central role of the limbic-motor interface in the pathophysiology of TS. Nonetheless, the true neuropathology of TS remains elusive, even though significant advances have been made in understanding complex interconnected circuitries within the limbic system and basal ganglia. Neuropathologic and neuroimaging studies—plagued by small samples, clinical heterogeneity, and a number of interpretative problems—are generally supportive of pathology within the orbitofrontal cortex, striatum, and their efferent projections in TS. The specific patterns of abnormalities vary widely across these studies, clouding attempts to define a unifying neuropathology for this disorder. Converging yet circumstantial evidence for frontal cortical, and basal ganglia pathology in TS comes also from studies infields ranging from neuroimmunology to neuropsychology, and from the clinical overlap between TS and disorders such as obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, and Sydenhams chorea. As a “model” neuropsychiatric disorder, TS has stimulated advances in several areas of neurobiology research, yet we still await a real understanding of its pathophysiology in order to move from empirically driven therapeutics to the development of targeted effective treatments.
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22

Graham, Eileen K., Bryan D. James, Kathryn L. Jackson, Emily C. Willroth, Patricia Boyle, Robert Wilson, David A. Bennett, and Daniel K. Mroczek. "Associations Between Personality Traits and Cognitive Resilience in Older Adults." Journals of Gerontology: Series B 76, no. 1 (September 24, 2020): 6–19. http://dx.doi.org/10.1093/geronb/gbaa135.

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Abstract Objectives The goal of this paper was to examine associations between personality traits and resilience to neuropathologic burden. Method Using data from the Religious Orders Study and the Rush Memory and Aging Project, we identified a total of 1,375 participants with personality, cognitive, and post-mortem neuropathology data. We regressed cognition onto pathology and extracted the residuals as an indicator of cognitive resilience. We then modeled the effect of Big Five personality traits on cognitive resilience, adjusting for demographics, APOE status, medical comorbidities, and cognitive activity. The analytic plan was preregistered prior to data access or analysis, and all scripts and outputs are available online. Results Higher neuroticism was associated with greater vulnerability to pathology. Results from exploratory analyses suggest that higher conscientiousness was associated with less cognitive decline relative to the amount of pathology, or greater resilience. Education and cognitive activity did not moderate these associations. Discussion Personality may have a pathoplastic effect on neuropathology, as low neuroticism and high conscientiousness are associated with better function despite neuropathologic burden.
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23

Henriksen, Jonathan, Teresa Kolognizak, Tracy Houghton, Steve Cherne, Daisy Zhen, Patrick J. Cimino, Caitlin S. Latimer, et al. "Rapid Validation of Telepathology by an Academic Neuropathology Practice During the COVID-19 Pandemic." Archives of Pathology & Laboratory Medicine 144, no. 11 (June 18, 2020): 1311–20. http://dx.doi.org/10.5858/arpa.2020-0372-sa.

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Context.— The coronavirus disease 19 (COVID-19) pandemic is placing unparalleled burdens on regional and institutional resources in medical facilities across the globe. This disruption is causing unprecedented downstream effects to traditionally established channels of patient care delivery, including those of essential anatomic pathology services. With Washington state being the initial North American COVID-19 epicenter, the University of Washington in Seattle has been at the forefront of conceptualizing and implementing innovative solutions in order to provide uninterrupted quality patient care amidst this growing crisis. Objective.— To conduct a rapid validation study assessing our ability to reliably provide diagnostic neuropathology services via a whole slide imaging (WSI) platform as part of our departmental COVID-19 planning response. Design.— This retrospective study assessed diagnostic concordance of neuropathologic diagnoses rendered via WSI as compared to those originally established via traditional histopathology in a cohort of 30 cases encompassing a broad range of neurosurgical and neuromuscular entities. This study included the digitalization of 93 slide preparations, which were independently examined by groups of board-certified neuropathologists and neuropathology fellows. Results.— There were no major or minor diagnostic discrepancies identified in either the attending neuropathologist or neuropathology trainee groups for either the neurosurgical or neuromuscular case cohorts. Conclusions.— Our study demonstrates that accuracy of neuropathologic diagnoses and interpretation of ancillary preparations via WSI are not inferior to those generated via traditional microscopy. This study provides a framework for rapid subspecialty validation and deployment of WSI for diagnostic purposes during a pandemic event.
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24

Shaffer, Rachel M., Ge Li, Sara D. Adar, C. Dirk Keene, Caitlin S. Latimer, Paul K. Crane, Eric B. Larson, Joel D. Kaufman, Marco Carone, and Lianne Sheppard. "Fine Particulate Matter and Markers of Alzheimer’s Disease Neuropathology at Autopsy in a Community-Based Cohort." Journal of Alzheimer's Disease 79, no. 4 (February 16, 2021): 1761–73. http://dx.doi.org/10.3233/jad-201005.

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Background: Evidence links fine particulate matter (PM2.5) to Alzheimer’s disease (AD), but no community-based prospective cohort studies in older adults have evaluated the association between long-term exposure to PM2.5 and markers of AD neuropathology at autopsy. Objective: Using a well-established autopsy cohort and new spatiotemporal predictions of air pollution, we evaluated associations of 10-year PM2.5 exposure prior to death with Braak stage, Consortium to Establish a Registry for AD (CERAD) score, and combined AD neuropathologic change (ABC score). Methods: We used autopsy specimens (N = 832) from the Adult Changes in Thought (ACT) study, with enrollment ongoing since 1994. We assigned long-term exposure at residential address based on two-week average concentrations from a newly developed spatiotemporal model. To account for potential selection bias, we conducted inverse probability weighting. Adjusting for covariates with tiered models, we performed ordinal regression for Braak and CERAD and logistic regression for dichotomized ABC score. Results: 10-year average (SD) PM2.5 from death across the autopsy cohort was 8.2 (1.9) μg/m3. Average age (SD) at death was 89 (7) years. Each 1μg/m3 increase in 10-year average PM2.5 prior to death was associated with a suggestive increase in the odds of worse neuropathology as indicated by CERAD score (OR: 1.35 (0.90, 1.90)) but a suggestive decreased odds of neuropathology as defined by the ABC score (OR: 0.79 (0.49, 1.19)). There was no association with Braak stage (OR: 0.99 (0.64, 1.47)). Conclusion: We report inconclusive associations between PM2.5 and AD neuropathology at autopsy among a cohort where 94% of individuals experienced 10-year exposures below the current EPA standard. Prior studies of AD risk factors and AD neuropathology are similarly inconclusive, suggesting alternative mechanistic pathways for disease or residual confounding.
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25

Paradise, Matthew B., Claire E. Shepherd, Wei Wen, and Perminder S. Sachdev. "Neuroimaging and neuropathology indices of cerebrovascular disease burden." Neurology 91, no. 7 (July 18, 2018): 310–20. http://dx.doi.org/10.1212/wnl.0000000000005997.

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ObjectiveTo systematically review the literature on the use of both neuroimaging and neuropathologic indices of cerebrovascular disease (CVD) burden, as estimation of this burden could have multiple benefits in the diagnosis and prognosis of cognitive impairment and dementia.MethodsMEDLINE and EMBASE databases were searched (inception to June 2017) to obtain and then systematically review all pertinent neuroimaging and neuropathology studies, where an index of CVD was developed or tested.ResultsTwenty-five neuroimaging articles were obtained, which included 4 unique indices. These utilized a limited range of CVD markers from mainly structural MRI, most commonly white matter hyperintensities (WMH), cerebral microbleeds, and dilated perivascular spaces. Weighting of the constituent markers was often coarse. There were 7 unique neuropathology indices, which were heterogeneous in their regions sampled and lesions examined.ConclusionThere is increasing interest in indices of total CVD burden that incorporate multiple lesions, as traditional individual markers of CVD such as WMH only provide limited information. Neuropathologic indices are needed to validate neuroimaging findings. The studies clearly demonstrated proof of concept that information from multiple imaging measures of CVD provide more information, including a stronger association with cognitive impairment and dementia, than that provided by a single measure. There has been limited exploration of the psychometric properties of published indices and no comparison between indices. Further development of indices is recommended, including the use of data from diffusion tensor and perfusion imaging.
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26

Misser, S. K., and J. F. Roos. "Paediatric neuropathology." South African Journal of Radiology 15, no. 3 (August 15, 2011): 101. http://dx.doi.org/10.4102/sajr.v15i3.381.

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27

Shankar, SK. "Neuropathology series." Annals of Indian Academy of Neurology 10, no. 2 (2007): 68. http://dx.doi.org/10.4103/0972-2327.33212.

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28

Squier, Marian V. "The Neuropathology." AVMA Medical & Legal Journal 4, no. 3 (May 1998): 81–88. http://dx.doi.org/10.1177/135626229800400304.

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29

Moore, Josephine C. "Neonatal Neuropathology." Physical & Occupational Therapy In Pediatrics 6, no. 3-4 (January 1986): 55–90. http://dx.doi.org/10.1080/j006v06n03_03.

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30

Hart, Michael N. "Developmental Neuropathology." Journal of Neuropathology & Experimental Neurology 64, no. 7 (July 2005): 648. http://dx.doi.org/10.1097/01.jnen.0000171655.62954.f6.

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31

Lantos, P. "Diagnostic Neuropathology." Journal of Neurology, Neurosurgery & Psychiatry 52, no. 9 (September 1, 1989): 1120. http://dx.doi.org/10.1136/jnnp.52.9.1120-a.

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32

Janota, I. "Greenfield's Neuropathology." Journal of Clinical Pathology 46, no. 1 (January 1, 1993): 95–96. http://dx.doi.org/10.1136/jcp.46.1.95-f.

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33

Geddes, J. F. "Greenfield's Neuropathology." Journal of Clinical Pathology 50, no. 9 (September 1, 1997): 798. http://dx.doi.org/10.1136/jcp.50.9.798-a.

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34

Robson, Keith. "Neuropathology Techniques." Neuropathology and Applied Neurobiology 31, no. 2 (April 2005): 204–5. http://dx.doi.org/10.1111/j.1365-2990.2005.00585.x.

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35

Mazanti, I. "Forensic Neuropathology." Neuropathology and Applied Neurobiology 33, no. 3 (June 2007): 364–66. http://dx.doi.org/10.1111/j.1365-2990.2007.00808.x.

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36

&NA;, &NA;. "Neuropathology Review." American Journal of Surgical Pathology 17, no. 12 (December 1993): 1303. http://dx.doi.org/10.1097/00000478-199312000-00015.

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37

Moore, Josephine. "Neonatal Neuropathology." Physical & Occupational Therapy In Pediatrics 6, no. 3 (December 17, 1986): 55–90. http://dx.doi.org/10.1300/j006v06n03_03.

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38

Leetsma, J. E., and Amy Martin. "Forensic Neuropathology." Therapeutic Drug Monitoring 11, no. 1 (January 1989): 115. http://dx.doi.org/10.1097/00007691-198901000-00027.

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39

Fenichel, Gerald. "Developmental Neuropathology." Cognitive and Behavioral Neurology 19, no. 2 (June 2006): 117. http://dx.doi.org/10.1097/01.wnn.0000213904.67450.8e.

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40

Palmer, Cheryl Ann. "NEUROPATHOLOGY REVIEW." Neuro-Oncology 4, no. 1 (January 1, 2002): 49–50. http://dx.doi.org/10.1093/neuonc/4.1.49.

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41

Lantos, P. "Greenfield's Neuropathology." Journal of Neurology, Neurosurgery & Psychiatry 48, no. 5 (May 1, 1985): 496. http://dx.doi.org/10.1136/jnnp.48.5.496.

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42

Jellinger, K. A. "Neuropathology Techniques." European Journal of Neurology 11, no. 10 (October 2004): 719. http://dx.doi.org/10.1111/j.1468-1331.2004.00834.x.

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Jellinger, K. A. "Developmental Neuropathology." European Journal of Neurology 12, no. 8 (August 2005): 663. http://dx.doi.org/10.1111/j.1468-1331.2005.01040.x.

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Jellinger, K. A. "Forensic Neuropathology." European Journal of Neurology 16, no. 2 (February 2009): e23-e23. http://dx.doi.org/10.1111/j.1468-1331.2008.02438.x.

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Jellinger, K. A., and C. Bancher. "AD neuropathology." Neurology 46, no. 4 (April 1, 1996): 1186. http://dx.doi.org/10.1212/wnl.46.4.1186-b.

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46

Leech, R. W. "Pediatric Neuropathology." Neurology 48, no. 3 (March 1, 1997): 793–94. http://dx.doi.org/10.1212/wnl.48.3.793-b.

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47

Wharton, S. B. "Neuropathology Techniques." Histopathology 45, no. 6 (December 2004): 641. http://dx.doi.org/10.1111/j.1365-2559.2004.01965.x.

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48

Reichard, R. Ross. "Autopsy Neuropathology." Academic Forensic Pathology 2, no. 1 (March 2012): x—xi. http://dx.doi.org/10.1177/192536211200200103.

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49

Hart, Michael. "Greenfield's Neuropathology." Journal of Neuropathology & Experimental Neurology 67, no. 8 (August 2008): 828.1–828. http://dx.doi.org/10.1097/nen.0b013e3181839bfd.

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50

Burger, Peter C. "Diagnostic Neuropathology." American Journal of Clinical Pathology 92, no. 3 (September 1, 1989): 393–94. http://dx.doi.org/10.1093/ajcp/92.3.393a.

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