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Transmembrane protein 106B amyloid is a potential off-target molecule of tau PET tracers in the choroid plexus

2024· article· en· W4404902368 on OpenAlexaff
Yuka Yokoyama, Ryuichi Harada, Kaede Kudo, Ren Iwata, Yukitsuka Kudo, Nobuyuki Okamura, Shozo Furumoto

Bibliographic record

VenueNuclear Medicine and Biology · 2024
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsInstitute of Aging
FundersJapan Science and Technology AgencyJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyJapan Agency for Medical Research and Development
KeywordsChoroid plexusTransmembrane proteinChemistryAmyloid (mycology)BiophysicsNeuroscienceBiochemistryBiologyCentral nervous systemReceptor

Abstract

fetched live from OpenAlex

PURPOSE: Tau positron emission tomography (PET) has become an essential tool for the clinical diagnosis of neurodegenerative diseases and the study of tau pathology in the brain. However, some tau tracers exhibit off-target binding in the basal ganglia, choroid plexus, and meninges. Recently, transmembrane protein 106B (TMEM106B) was identified to form novel amyloid filaments in the brain during aging. In this study, we explored the possibility that TMEM106B aggregates might be responsible for off-target binding of tau PET tracers in the choroid plexus. METHODS: F-labeled tau and amyloid tracers against choroid plexus tissues from postmortem human brains were evaluated through in vitro autoradiography and in vitro binding assays and compared with histochemical staining. RESULTS: F]flortaucipir demonstrated high affinities for collagenase A-treated choroid plexus homogenate containing transmembrane protein 106B aggregates. CONCLUSION: F]PM-PBB3 to the choroid plexus might result from binding to TMEM106B aggregates.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.317
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2024
Admission routes1
Has abstractyes

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