Evidence map›Paper›PMID 41000074›Full record

ReviewFrontiers in cell and developmental biology2025

Metabolic reprogramming in efferocytosis.

Qing Yan, Kuo Li, Lu Chen, Aowei Wang, Yingying Xi, Hui Xiao, Lei Yuan

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

7 authors.

Qing Yan *College of Life Sciences, Shaanxi Normal University, Xi'an, China.
Kuo Li *College of Life Sciences, Shaanxi Normal University, Xi'an, China.
Lu Chen *College of Life Sciences, Shaanxi Normal University, Xi'an, China.
Aowei Wang *College of Life Sciences, Shaanxi Normal University, Xi'an, China.
Yingying XiCollege of Life Sciences, Shaanxi Normal University, Xi'an, China.
Hui XiaoCollege of Life Sciences, Shaanxi Normal University, Xi'an, China.
Lei Yuan *College of Life Sciences, Shaanxi Normal University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efferocytosis refers to the process by which phagocytes specifically identify and eliminate apoptotic cells. This process is essential for both maintaining tissue homeostasis and suppressing inflammatory responses, as well as facilitating tissue repair. When phagocytes internalize apoptotic cells, which act as "nutrient packages," they undergo significant metabolic reprogramming. This reprogramming not only supplies energy and biosynthetic precursors necessary for engulfment but also critically influences the functional phenotype of phagocytes through complex molecular networks. These networks ultimately determine whether phagocytes adopt an anti-inflammatory resolution or a pathological pro-inflammatory state. This article offers a comprehensive analysis of the molecular regulatory mechanisms that underpin metabolic reprogramming during efferocytosis, aiming to elucidate the intricate regulatory networks formed by the interaction of metabolites as signaling molecules and classical signaling pathways. We examine how the three primary metabolic pathways-glucose, lipid, and amino acid metabolisms-are regulated by signals from efferocytosis and, in turn, modulate phagocyte function. A deeper understanding of the interplay between metabolic reprogramming and efferocytosis will provide a theoretical foundation and novel targets for treating diseases associated with impaired clearance of apoptotic cells.

Indexed as

apoptotic cell clearanceefferocytosisfatty acid oxidationglycolysismacrophagesmetabolic reprogramming

Identifiers

PMID41000074
PMCPMC12457674

What OpenQuestion holds

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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.