Evidence map›Paper›PMID 42345778›Full record

ArticleBiology2026

Hematopoietic Rejuvenation via Natural Senolytic NSPCC1 Delays Inflammatory Aging.

Wei Wang, Shenglong Yang, Rongjinlei Zhang, Yufang Wang, Zhen Zhang, Feng Xiao, Shu Wu, Zhenyu Ju, Ruikun He, Yuanlong Ge

Abstract read
In one paragraph

Article in Biology, 2026. 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

10 authors.

Wei WangState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.ORCID 0009-0000-2701-0522
Shenglong YangState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Rongjinlei ZhangState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Yufang WangBYHEALTH Institute of Nutrition & Health, Guangzhou 510663, China.
Zhen ZhangBYHEALTH Institute of Nutrition & Health, Guangzhou 510663, China.
Feng XiaoKey Laboratory of Regenerative Medicine of Ministry of Education, Institute of Aging and Regenerative Medicine, Department of Developmental & Regenerative Medicine, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Shu WuState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Zhenyu JuState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Ruikun HeBYHEALTH Institute of Nutrition & Health, Guangzhou 510663, China.ORCID 0000-0002-2292-8884
Yuanlong GeState Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.ORCID 0000-0003-1850-519X

Funding

National Natural Science Foundation of China 82230047National Natural Science Foundation of China 82271590the innovation team project of universities in Guangdong province 2023KCXTD004the National Key R&D Program of China 2021YFA1100103
6 · The paper itself

Abstract

Chronic inflammation accelerates the aging process, and targeted clearance of senescent cells shows potential in alleviating age-related decline. PCC1, a potent senescent cell clearance agent in grape seed extract (GSE), has limited applications due to its low oral bioavailability. This study introduced a novel GSE formulation, Natural Senolytics PCC1 (NSPCC1), which significantly enhanced PCC1 absorption and metabolic characteristics. Validation in two mouse aging models demonstrated that oral administration of NSPCC1 markedly extended lifespan and promoted healthy aging. The formulation improved the capacity for hematopoietic stem/progenitor cell differentiation and reduced age-related myeloid cell bias. Comprehensive histological analysis revealed attenuated aging phenotypes in bone marrow and skin, improved peripheral blood erythroid parameters, and a partial increase in blood antioxidant capacity, alongside reduced M1 macrophage infiltration and fibrosis in liver, kidney, and lung tissues. These effects were validated through histological assessments, including H&E, Masson, F4/80, and iNOS staining. This study highlighted the pivotal role of hematopoietic stem cells in aging and established NSPCC1 as a promising natural intervention for age-related pathologies. Its enhanced efficacy lays the groundwork for deeper exploration of natural products in aging biology and provides crucial support for the development of safe and effective anti-aging therapies.

Indexed as

anti-agingchronic inflammationhematopoietic stem cell senescenceinflammatory infiltrationNatural Senolytics

Identifiers

PMID42345778
PMCPMC13296190

What OpenQuestion holds

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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 OpenQuestion graph.