Evidence map›Paper›PMID 40643973›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Multiorgan transcriptomics in mice identifies immunoglobulin heavy constant mu (

Fan-Qian Yin, Xia-Yan Wang, Yong-Xuan Li, Kai-Jing Li, Si-Yu Ma, Meng-Jiao Lv, Zhen-Hua Liu, Wei-Xia Zhong, Yan Liu, Chuan-Fang Tang and 4 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Immunoglobulin G in aging and cancer.Frontiers in immunology · 2026
    Review
  4. Spatiotemporal mapping reveals Ccl8Clinical and translational medicine · 2025
    Article
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

14 authors.

Fan-Qian Yin *State Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Xia-Yan Wang *State Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Yong-Xuan LiState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Kai-Jing LiState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Si-Yu MaState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Meng-Jiao LvState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Zhen-Hua LiuState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Wei-Xia ZhongState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Yan LiuState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Chuan-Fang TangState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.
Hong-Shi LiuHeilongjiang Provincial Hospital, Harbin 150000, China.
Yuze LiHeilongjiang Provincial Hospital, Harbin 150000, China.
Fu-Hui XiaoState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.ORCID 0000-0001-7478-7801
Qing-Peng KongState Key Laboratory of Genetic Evolution and Animal Models, State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China.ORCID 0000-0002-6046-4494

Funding

CAS Project for Young Scientists in Basic Research YSBR-076High-level Talent Promotion and Training Project of Kunming 2020SCP001MOST | National Key Research and Development Program of China (NKPs) 2023YFC3603400MOST | National Natural Science Foundation of China (NSFC) 82371580MOST | National Natural Science Foundation of China (NSFC) 82430049Reserve Talent Project of Young and Middle-aged Academic and Technical Leaders in Yunnan Province 202305AC160029Yunnan Fundamental Research Projects 202201AS070080
6 · The paper itself

Abstract

Identifying aging-associated biomarkers applicable for multiple tissues is challenging but crucial for assessing tissue aging. Here, we obtained and analyzed 456 transcriptomes on 17 organs from 30 C57BL/6 J mice with different ages, revealing the consistently upregulated mRNAs of

Indexed as

AgingImmunoglobulin Heavy ChainsTranscriptomeAnimalsBiomarkersGene Expression ProfilingMaleMiceMice, Inbred C57BLRNA, MessengerBiomarkersImmunoglobulin Heavy ChainsRNA, Messengeraging biomarkerIghmtissue aging

Identifiers

PMID40643973
PMCPMC12280941

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.