Evidence map›Paper›PMID 39257378›Full record

ReviewZoological research2024

Experimental models for preclinical research in kidney disease.

Jin Miao, Huanhuan Zhu, Junni Wang, Jianghua Chen, Fei Han, Weiqiang Lin

Abstract readReview
In one paragraph

Review in Zoological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Jin MiaoKidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine.
Huanhuan ZhuKidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine.
Junni WangKidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine.
Jianghua ChenKidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine.
Fei HanKidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine.
Weiqiang LinDepartment of Nephrology, Center for Regeneration and Aging Medicine, Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, Zhejiang 322000, China. E-mail: wlin@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute kidney injury (AKI) and chronic kidney disease (CKD) are significant public health issues associated with a long-term increase in mortality risk, resulting from various etiologies including renal ischemia, sepsis, drug toxicity, and diabetes mellitus. Numerous preclinical models have been developed to deepen our understanding of the pathophysiological mechanisms and therapeutic approaches for kidney diseases. Among these, rodent models have proven to be powerful tools in the discovery of novel therapeutics, while the development of kidney organoids has emerged as a promising advancement in the field. This review provides a comprehensive analysis of the construction methodologies, underlying biological mechanisms, and recent therapeutic developments across different AKI and CKD models. Additionally, this review summarizes the advantages, limitations, and challenges inherent in these preclinical models, thereby contributing robust evidence to support the development of effective therapeutic strategies.

Indexed as

Disease Models, AnimalAcute Kidney InjuryAnimalsHumansKidney DiseasesRenal Insufficiency, ChronicAcute kidney injuryChronic kidney diseaseMouse models

Identifiers

PMID39257378
PMCPMC11491777

What OpenQuestion holds

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LicenceCC BY-NC
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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.