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Record W4281767317 · doi:10.21203/rs.3.rs-1696103/v1

Deficiency of IKKβ in neurons ameliorates Alzheimer’s disease pathology in APP- and tau-transgenic mice

2022· preprint· en· W4281767317 on OpenAlexfundno aff
Laura Schnöder, Wenqiang Quan, Ye Yu, Inge Tomic, Qinghua Luo, Wenlin Hao, Guoping Peng, Dong Li, Klaus Faßbender, Yang Liu

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersUniversität zu KölnChina Scholarship CouncilUniversity of TorontoAlzheimer Forschung InitiativeNational Natural Science Foundation of ChinaYouth Science Foundation of Jiangxi ProvinceUniversität des Saarlandes
KeywordsGenetically modified mouseMorris water navigation taskTau proteinNeuroinflammationTransgeneCell biologyPhosphorylationKinaseBiologyIκB kinaseAlzheimer's diseaseChemistryNeuroscienceMolecular biologyInternal medicineNF-κBHippocampusSignal transductionImmunologyMedicineBiochemistryInflammation

Abstract

fetched live from OpenAlex

Abstract Background: Alzheimer’s disease (AD) is pathologically characterized by extracellular deposition of amyloid β peptide (Aβ), intracellular neurofibrillary tangles (composed mainly of phosphorylated tau [p-tau]) and neuroinflammation. The pathogenic role of inflammatory activation in AD has been extensively studied; however, the underlying mechanisms remain unclear. In this project, we investigated how neuronal IKKβ/NF-kB regulates AD-associated pathologies in APP- and tau-transgenic AD mice. Methods: APP- and tau-transgenic mice were cross-bred with ikbkb-floxed and nex-cre knock-in mice to generate AD models with deletion of IKKβ specifically in neurons. After assessing cognitive function with the Morris water maze test, mice were analyzed for Aβ and p-tau levels, microglial numbers, transcription of inflammatory genes, apoptosis and synaptic protein levels in the brain by histological, biochemical and molecular biology methods. To explore pathogenic mechanisms, we analyzed the activity and/or protein levels of: 1) β- and γ-secretases, 2) tau-phosphorylating (e.g., GSK3β and p38α-MAPK) and dephosphorylating enzymes (e.g., PP2A and PP2B), and 3) autophagy-related proteins (e.g., LC3B, beclin1 and SQSTM1/p62). In addition, IKKβ-knockdown and wild-type SH-SY5Y cell lines were created to verify the in vivo results.Results: In APP-transgenic mice, neuronal deficiency of IKKβ decreased Aβ load, inflammatory activation, and apoptosis in the brain, and improved cognitive function and maintenance of synaptic proteins (e.g., PSD-95). IKKβ deficiency decreased BACE1 activity and protein in the brain and cultured neuronal cells. In tau-transgenic mice, neuronal deficiency of IKKβ decreased p-tau, shifted pro- to anti-inflammatory activation and inhibited autophagy in the brain. IKKβ deficiency increased expression of PP2A catalytic subunit isoform A, an enzyme dephosphorylating cerebral p-tau. However, deficiency of IKKβ in neurons did not alter the cognitive function and even increased apoptosis in the brain.Conclusions: Deficiency of IKKβ in neurons attenuates Aβ and p-tau loads in the brains of AD mice. As possible molecular mechanisms, IKKβ deficiency decreases BACE1 activity, thereby reducing Aβ production, and increases PP2A expression, promoting p-tau dephosphorylation. However, IKKβ deficiency protects neurons only in APP-transgenic mice, but not in tau-transgenic AD mice. Further studies are needed before IKKβ/NF-kB can be targeted for AD therapies.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.087
GPT teacher head0.416
Teacher spread0.329 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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