Evidence map›Paper›PMID 40809088›Full record

ArticlePNAS nexus2025

Differential expression of long-term depression, and synaptic tagging and capture in mouse hippocampal area CA2 synapses.

Zijun Wang, Lik-Wei Wong, Sreedharan Sajikumar

Abstract read
In one paragraph

Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zijun WangDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.ORCID https://orcid.org/0000-0001-8572-4603
Lik-Wei WongDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.
Sreedharan SajikumarDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.ORCID https://orcid.org/0000-0002-5761-8982

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CA2 hippocampal neurons have received renewed interest due to their unique functions and plasticity properties that differ between synapses within the same neuronal population. However, detailed studies on long-term depression (LTD) in CA2 pyramidal neurons are lacking. In this study, LTD was induced and characterized at both Schaffer collateral-CA2 (SC-CA2) and entorhinal cortex-CA2 (EC-CA2) synapses in young, male mice. This LTD was found to be dependent on N-methyl-D-aspartate receptors, protein synthesis, and p75 neurotrophin receptors. However, weaker stimulations could only induce early LTD in EC-CA2 but not SC-CA2 synapses, consistent with its "plasticity-resistant" nature. CA2 LTD is capable of undergoing heterosynaptic synaptic tagging and capture (STC), although the machinery involved differs between SC-CA2 and EC-CA2 synapses. SC-CA2, but not EC-CA2, requires precursor brain-derived neurotrophic factor activity to maintain LTD. Subsequently, quantitative shotgun proteomics analysis yields complexin-2 as a strong candidate plasticity-related product involved in LTD in the CA2. These results reveal interesting differences in STC machinery between synaptic populations of a common set of neurons, enhancing our understanding of hippocampal circuitry involving the CA2. Interesting implications regarding the heterogeneous biochemical makeup of CA2 pyramidal neurons and fundamental STC theory that arise as a consequent of our results are also discussed further.

Indexed as

CA2 regionCPLX2long-term depressionp75NTRsynaptic tagging and capture

Identifiers

PMID40809088
PMCPMC12344489

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.