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Record W3130569924 · doi:10.1111/jnc.15323

Hippocampal hyperactivity in a rat model of Alzheimer’s disease

2021· article· en· W3130569924 on OpenAlexaffabout
Liudmila Sosulina, Manuel Mittag, Hans‐Rüdiger Geis, Kerstin Hoffmann, Igor Klyubin, Yingjie Qi, Julia Steffen, Detlef Friedrichs, Niklas Henneberg, Falko Fuhrmann, Daniel Justus, Kevin Keppler, A. Claudio Cuello, Michael J. Rowan, Martin Fuhrmann, Stefan Remy

Bibliographic record

VenueJournal of Neurochemistry · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill University
FundersDeutsche ForschungsgemeinschaftScience Foundation Ireland
KeywordsHippocampal formationNeuroscienceHippocampusInhibitory postsynaptic potentialAlzheimer's diseaseExtracellularIn vivoGenetically modified mouseBiologyTransgeneDiseaseMedicinePathologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Neuronal network dysfunction is a hallmark of Alzheimer's disease (AD). However, the underlying pathomechanisms remain unknown. We analyzed the hippocampal micronetwork in transgenic McGill‐R‐Thy1‐APP rats (APPtg) at the beginning of extracellular amyloid beta (Aβ) deposition. We established two‐photon Ca 2+ ‐imaging in vivo in the hippocampus of rats and found hyperactivity of CA1 neurons. Patch‐clamp recordings in brain slices in vitro revealed increased neuronal input resistance and prolonged action potential width in CA1 pyramidal neurons. We did neither observe changes in synaptic inhibition, nor in excitation. Our data support the view that increased intrinsic excitability of CA1 neurons may precede inhibitory dysfunction at an early stage of Aβ‐deposition and disease progression. image

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.098
GPT teacher head0.365
Teacher spread0.267 · 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

Citations54
Published2021
Admission routes2
Has abstractyes

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