Evidence map›Paper›PMID 42091731›Full record

ArticleFunctional & integrative genomics2026

The sleeping kidney: microRNA expression profiling of kidney tissue during daily torpor in mice.

Panyi Yang, Saif Rehman, Jing Zhang, Ziyin Wang, Zihan Zhao, Bofang Zhang, Kenneth B Storey, Yuhong Hu, Hui Wang

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Article in Functional & integrative genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

9 authors.

Panyi Yang *Hebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, Hebei Collaborative Innovation Center for Eco-Environment, Hebei Research Center of the Basic Discipline of Cell Biology, Ministry of Education Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, Hebei, China.ORCID http://orcid.org/0009-0008-1049-264X
Saif Rehman *Department of Biology, Carleton University, Ottawa, ON, K1S 5B6, Canada.ORCID http://orcid.org/0009-0006-0659-9896
Jing ZhangDepartment of Biology, Carleton University, Ottawa, ON, K1S 5B6, Canada.ORCID http://orcid.org/0000-0002-6076-7321
Ziyin WangHebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, Hebei Collaborative Innovation Center for Eco-Environment, Hebei Research Center of the Basic Discipline of Cell Biology, Ministry of Education Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, Hebei, China.ORCID http://orcid.org/0009-0009-0133-5324
Zihan ZhaoHebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, Hebei Collaborative Innovation Center for Eco-Environment, Hebei Research Center of the Basic Discipline of Cell Biology, Ministry of Education Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, Hebei, China.ORCID http://orcid.org/0009-0000-6585-3547
Bofang ZhangHebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, Hebei Collaborative Innovation Center for Eco-Environment, Hebei Research Center of the Basic Discipline of Cell Biology, Ministry of Education Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, Hebei, China.ORCID http://orcid.org/0009-0008-2112-2767
Kenneth B StoreyDepartment of Biology, Carleton University, Ottawa, ON, K1S 5B6, Canada.ORCID http://orcid.org/0000-0002-7363-1853
Yuhong HuInstrumental Analysis Center, Hebei Normal University, Shijiazhuang, 050024, Hebei, China. huyuhong2004@163.com.ORCID http://orcid.org/0000-0001-7423-1643
Hui WangHebei Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, Hebei Collaborative Innovation Center for Eco-Environment, Hebei Research Center of the Basic Discipline of Cell Biology, Ministry of Education Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, Hebei, China. whui1981@163.com.ORCID http://orcid.org/0000-0002-0272-0015

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNA (miRNA), a class of short non-coding RNA, serves as a metabolically cheap and fast acting mechanism to inhibit translation of complementary mRNA. These molecules play a central role in regulating metabolic changes during torpor in small mammals, such as the house mouse (Mus musculus). The present study sequenced mouse kidney RNA to identify changes in miRNA expression in kidney, comparing active control mice (C57BL/6 strain) with mice in varying stages of torpor. Out of a total 962 miRNAs, 82 were differentially expressed when comparing torpid states to the control with 65, 14, and 2 miRNAs differentially expressed in deep torpor, early torpor, and recovery from torpor mice, respectively. In silico analysis of these targets demonstrated a clear downregulation of gene sets associated with cancer and active metabolism. This suggests that miRNA may play important roles in suppressing cell division and proliferation during torpor, along with maintaining a hypometabolic state. Machine learning techniques identified two specific miRNAs (miR-101c, miR-101a-3p) that can strongly distinguish between torpid and active states in kidney among other differentially regulated miRNA. The present study highlights the role of miRNA in transcriptional regulation of cell signaling and metabolic pathways in kidney throughout mouse torpor.

Indexed as

KidneyMicroRNAsTorporAnimalsGene Expression ProfilingMaleMiceMice, Inbred C57BLMicroRNAsFunctional genomicsHeterothermyHypometabolismMiRNAMus musculusTorpor

Identifiers

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Registered trials

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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 Socratic graph.