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Record W4372211753 · doi:10.1016/j.celrep.2023.112478

Nanoscale and functional heterogeneity of the hippocampal extracellular space

2023· article· en· W4372211753 on OpenAlexfundno aff
Diego Grassi, Agata Idziak, Antony Lee, Ivo Calaresu, Jean‐Baptiste Sibarita, Laurent Cognet, U. Valentin Nägerl, Laurent Groc

Bibliographic record

VenueCell Reports · 2023
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsnot available
FundersConseil Régional AquitaineUniversité de BordeauxCentre National de la Recherche ScientifiqueFondation ARC pour la Recherche sur le CancerFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleEuropean Research CouncilHuman Frontier Science ProgramH2020 European Research CouncilAgence Nationale de la RechercheOttawa Hospital Research Institute
KeywordsHippocampal formationExtracellularExtracellular matrixHippocampusNeuroscienceNanoscopic scaleBiologyCell biologyNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

The extracellular space (ECS) and its constituents play a crucial role in brain development, plasticity, circadian rhythm, and behavior, as well as brain diseases. Yet, since this compartment has an intricate geometry and nanoscale dimensions, its detailed exploration in live tissue has remained an unmet challenge. Here, we used a combination of single-nanoparticle tracking and super-resolution microscopy approaches to map the nanoscale dimensions of the ECS across the rodent hippocampus. We report that these dimensions are heterogeneous between hippocampal areas. Notably, stratum radiatum CA1 and CA3 ECS differ in several characteristics, a difference that gets abolished after digestion of the extracellular matrix. The dynamics of extracellular immunoglobulins vary within these areas, consistent with their distinct ECS characteristics. Altogether, we demonstrate that ECS nanoscale anatomy and diffusion properties are widely heterogeneous across hippocampal areas, impacting the dynamics and distribution of extracellular molecules.

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 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 score0.070
Threshold uncertainty score0.231

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)0.0000.000

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 head0.030
GPT teacher head0.234
Teacher spread0.204 · 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.

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

Citations18
Published2023
Admission routes1
Has abstractyes

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