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Record W2948768968 · doi:10.1073/pnas.1902672116

Specific factors in blood from young but not old mice directly promote synapse formation and NMDA-receptor recruitment

2019· article· en· W2948768968 on OpenAlexfundno aff
Kathlyn J. Gan, Thomas C. Südhof

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchCanadian HIV Trials Network, Canadian Institutes of Health Research
KeywordsSynapseSynapse formationNMDA receptorNeuroscienceCognitionCognitive declineBiologyYoung adultReceptorPsychologyMedicineDevelopmental psychologyInternal medicineDementiaGenetics

Abstract

fetched live from OpenAlex

-methyl-d-aspartate (NMDA) receptors, thereby increasing synaptic connectivity. Mass spectrometry revealed that thrombospondin-4 (THBS4) and SPARC-like protein 1 (SPARCL1) were enriched in serum from young mice. Strikingly, recombinant THBS4 and SPARCL1 both increased dendritic arborization and doubled synapse numbers in cultured neurons. In addition, SPARCL1 but not THBS4 tripled NMDA receptor-mediated synaptic responses. Thus, at least two proteins enriched in young blood, THBS4 and SPARCL1, directly act on neurons as synaptogenic factors. These proteins may represent rejuvenation factors that enhance synaptic connectivity by increasing dendritic arborization, synapse formation, and synaptic transmission.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.285
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 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

Citations114
Published2019
Admission routes1
Has abstractyes

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