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Record W4403479144 · doi:10.1093/brain/awae325

Amyloid-β predominant Alzheimer’s disease neuropathologic change

2024· article· en· W4403479144 on OpenAlexafffund
Gábor G. Kovács, Yuriko Katsumata, Xian Wu, Khine Zin Aung, David W. Fardo, Shelley L. Forrest, James D. Bowen, Paul K. Crane, Gail P. Jarvik, C. Dirk Keene, Eric B. Larson, Wayne C. McCormick, Susan M. McCurry, Shubhabrata Mukherjee, Neil W. Kowall, Ann C. McKee, Robert A. Stern, Clinton T. Baldwin, Lindsay A. Farrer, Gyungah Jun, Kathryn L. Lunetta, Lawrence S. Honig, Jean Paul Vonsattel, Jennifer Williamson, Scott A. Small, Sandra Barral, Christiane Reitz, Badri N. Vardarajan, Richard Mayeux, James R. Burke, Christine M. Hulette, Kathleen A. Welsh‐Bohmer, Marla Gearing, James J. Lah, Allan I. Levey, Thomas S. Wingo, Liana G. Apostolova, Martin R. Farlow, Bernardino Ghetti, Andrew J. Saykin, Salvatore Spina, Kelley Faber, Tatiana M. Foroud, Marilyn Albert, Constantine G. Lyketsos, Juan C. Troncoso, Matthew P. Frosch, Robert C. Green, John H. Growdon, Bradley T. Hyman, Rudolph E. Tanzi, Huntington Potter, Dennis W. Dickson, Nilüfer Ertekin‐Taner, Neill R Graff-Radford, Joseph E. Parisi, Ronald C. Petersen, Bradley F Boeve, Mariet Allen, Minerva M. Carrasquillo, Steven G. Younkin, Ranjan Duara, Joseph D. Buxbaum, Alison Goate, Mary Sano, Arjun V. Masurkar, Thomas Wısnıewskı, Eileen H. Bigio, Marsel Mesulam, Sandra Weıntraub, Robert Vassar, Jeffrey Kaye, Joseph F. Quinn, Randall L. Woltjer, Lisa L. Barnes, Lei Yu, Denis A. Evans, Victor W. Henderson, Kenneth B. Fallon, Lindy E. Harrell, Daniel Marson, Erik D. Roberson, Charles DeCarli, Lee‐Way Jin, John Olichney, Ronald Kim, Frank M. LaFerla, Edwin S. Monuki, Elizabeth Head, David L. Sultzer, Daniel H. Geschwind, Harry V. Vinters, Marie‐Françoise Chesselet, Douglas Galasko, James Brewer, Adam L. Boxer, Anna Karydas, Joel H. Kramer, Bruce L. Miller, Howard J. Rosen, William W. Seeley, Jeffrey M. Burns, Russell H. Swerdlow, Linda J. Van Eldik, Roger L. Albin, Andrew P. Lieberman, Henry L. Paulson, Steven E. Arnold, John Q. Trojanowski, Vivianna M Van Deerlin, Laura B. Cantwell, Amanda P Kuzma, John Malamon, Adam C. Naj, Liming Qu, Gerard D. Schellenberg, Otto Valladares, Li-San Wang, Yi Zhao, Ronald L. Hamilton, M. Ilyas Kamboh, James T. Becker, Chuanhai Cao, Raj Ashok, Amanda Smith, Helena Chui, Carol A. Miller, John M. Ringman, Lon S. Schneider, Thomas Bird, Joshua A. Sonnen, Chang‐en Yu, Thomas Grabowsk, Elaine R. Peskind, Murray A. Raskind, Ge Li, Debby W. Tsuang, Sanjay Asthana, Craig Atwood, Cynthia M. Carlsson, Mark A. Sager, Nathaniel A. Chin, Suzanne Craft, Nigel J Cairns, John C. Morris, Carlos Cruchaga, Stephen M. Strittmatter, Eric M. Reiman, Thomas G. Beach, Matthew J. Huentelman, John Hardy, John Kauwe, Håkon Håkonarson, Deborah Blacker, Thomas J. Montine, William S. Bush, Jonathan L. Haines, Alan J Lerner, Xiongwei Zhou, Gary W. Beecham, Regina M. Carney, Michael L. Cuccaro, John R. Gilbert, Kara L. Hamilton‐Nelson, Brian W. Kunkle, Eden R. Martin, Margaret A Pericak‐Vance, Jeffery M. Vance, Amanda Myers, James B. Leverenz, Philip L. De Jager, Mindy J. Katz, Richard Lipton, Valory Pavlik, Paul J. Massman, Eveleen Darby, Monica Rodriguear, Aisha Khaleeq, Donald R. Royall, Alan Stevens, Marcia G. Ory, John C. DeToledo, Henrick Wilms, Kim G. Johnson, Victòria Aurora Ferrer Pérez, Michelle L. Hernandez, Kirk C. Wilhelmsen, Jeffrey L. Tilson, Scott Chasse, Robert C. Barber, Thomas Fairchild, Sid E. O’Bryant, Janice Knebl, James Hall, Leigh Johnson, Douglas Mains, Lisa Alvarez, Adriana C. Gamboa, David Paydarfar, John Bertelson, Martin Woon, Gayle Ayres, Alyssa Aguirre, Raymond F. Palmer, Marsha Polk, Perrie M. Adams, Ryan M. Huebinger, Joan Reisch, Roger N. Rosenberg, C. Munro Cullum, Benjamin Williams, Mary Quiceno, Linda S. Hynan, Janet L. Smith, Barb Davis, Trung Nguyen, Ekaterina Rogaeva, Peter St George‐Hyslop, Peter T. Nelson

Bibliographic record

VenueBrain · 2024
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsOccupational Cancer Research CentreUniversity of TorontoUniversity Health Network
FundersNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Institute of Mental HealthNational Institute on AgingUniversity of California, San FranciscoStichting MS ResearchCanadian Institutes of Health ResearchPfizerUniversity of WashingtonUniversity of California, Los AngelesGenentechNational Institutes of HealthH. Lundbeck A/SFoundation for the National Institutes of HealthUniversity of Southern CaliforniaEisaiNational Cancer InstituteMedical Research CouncilServierNewcastle UniversityNorthern California Institute for Research and EducationUniversity of California, San DiegoJohns Hopkins UniversityYork UniversityUniversity of MiamiNorthwestern UniversityBiogenBioClinicaEmory UniversityU.S. Department of Veterans AffairsUniversity of PennsylvaniaVanderbilt UniversityMassachusetts General HospitalNovartis Pharmaceuticals CorporationIXICOUniversity of PittsburghOffice of Research and DevelopmentAlzheimer's AssociationAlzheimer's Research TrustU.S. Department of DefenseHersenstichtingEli Lilly and CompanyNorth Bristol NHS TrustBristol-Myers SquibbWellcome TrustUniversitat de BarcelonaRush UniversityMeso Scale Diagnostics
KeywordsAlzheimer's diseaseAmyloid (mycology)MedicineNeuropathologyDiseasePathologyNeurosciencePsychology

Abstract

fetched live from OpenAlex

Different subsets of Alzheimer's disease neuropathologic change (ADNC), including the intriguing set of individuals with severe/widespread amyloid-β (Aβ) plaques but no/mild tau tangles [Aβ-predominant (AP)-ADNC], may have distinct genetic and clinical features. Analysing National Alzheimer's Coordinating Center data, we stratified 1187 participants into AP-ADNC (n = 95), low Braak primary age-related tauopathy (PART; n = 185), typical-ADNC (n = 832) and high-Braak PART (n = 75). AP-ADNC differed in some clinical features and genetic polymorphisms in the APOE, SNX1, WNT3/MAPT and IGH genes. We conclude that AP-ADNC differs from classical ADNC with implications for in vivo studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.081
GPT teacher head0.354
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2024
Admission routes2
Has abstractyes

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