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Record W2153323774 · doi:10.1093/cercor/bhi086

Growth of Neurites toward Neurite– Neurite Contact Sites Increases Synaptic Clustering and Secretion and Is Regulated by Synaptic Activity

2005· article· en· W2153323774 on OpenAlexaff
Joshua Cove, Pablo Blinder, Elia Abi‐Jaoude, Myriam Lafrenière‐Roula, Luc Devroye, Danny Baranes

Bibliographic record

VenueCerebral Cortex · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill UniversityUniversity of ManitobaUniversity of Toronto
FundersBen-Gurion University of the Negev
KeywordsNeuriteNeuroscienceSynaptophysinHippocampusBiologyImmunohistochemistry

Abstract

fetched live from OpenAlex

The integrative properties of dendrites are determined by several factors, including their morphology and the spatio-temporal patterning of their synaptic inputs. One of the great challenges is to discover the interdependency of these two factors and the mechanisms which sculpt dendrites' fine morphological details. We found a novel form of neurite growth behavior in neuronal cultures of the hippocampus and cortex, when axons and dendrites grew directly toward neurite-neurite contact sites and crossed them, forming multi-neurite intersections (MNIs). MNIs were found at a frequency higher than obtained by computer simulations of randomly distributed dendrites, involved many of the dendrites and were stable for days. They were formed specifically by neurites originating from different neurons and were extremely rare among neurites of individual neurons or among astrocytic processes. Axonal terminals were clustered at MNIs and exhibited higher synaptophysin content and release capability than in those located elsewhere. MNI formation, as well as enhancement of axonal terminal clustering and secretion at MNIs, was disrupted by inhibitors of synaptic activity. Thus, convergence of axons and dendrites to form MNIs is a non-random activity-regulated wiring behavior which shapes dendritic trees and affects the location, clustering level and strength of their presynaptic inputs.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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 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

Citations24
Published2005
Admission routes1
Has abstractyes

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