Evidence map›Paper›PMID 40520178›Full record

ReviewFrontiers in pharmacology2025

Targeting the programmed cell death signaling mechanism with natural products for the treatment of acute pancreatitis: a review.

Xuehuan Liu, Baolei Dou, Qingjun Zhu, Chuanguo Liu

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

4 authors.

Xuehuan LiuThe Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China.
Baolei DouCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
Qingjun ZhuInnovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China.
Chuanguo LiuThe Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute pancreatitis (AP) is a common critical disease in clinical practice, characterized by acute onset, rapid progression, aggressive conditions, and high lethality. Pancreatic acinar cell death is a central event in the pathological process of AP and a key factor in determining the extent of local or systemic inflammatory injury and overall prognosis. Programmed cell death (PCD) is a form of active cell death regulated by multiple genes, including apoptosis, autophagy, ferroptosis, pyroptosis, and necroptosis. PCD plays a critical role in eliminating unwanted organisms and damaged cells, which is of great significance. Numerous studies have demonstrated a strong association between various forms of PCD and AP, and targeted interventions in PCD signaling pathways and key targets can influence the progression of AP. Furthermore, existing research indicates that natural products sourced from plants, fruits, and vegetables exhibit considerable potential in targeting and regulating PCD for the treatment of AP. Therefore, this paper focuses on summarizing the common types of PCD in AP and discusses the specific signaling pathways and key targets reported in the treatment of AP using natural products. This review aims to provide a reference for natural products in guiding AP treatment and to lay the foundation for developing new drugs to effectively prevent and manage AP.

Indexed as

acute pancreatitisnatural productsprogrammed cell deathsignaling pathwaystherapy

Identifiers

PMID40520178
PMCPMC12162924

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.