Evidence map›Paper›PMID 41122466›Full record

ArticleCancer innovation2025

Challenges in the Immune System: Mesoscale and Mesoregime Complexity.

Ying Ren, Ai-Guo Wu, Yu Shi, Yi-Fang Ping, Jing-Hai Li, Xiu-Wu Bian

Abstract read
In one paragraph

Article in Cancer innovation, 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. Article
  3. Article
  4. Oncology research · 2026
    Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ying RenState Key Laboratory of Mesoscience and Engineering, Institute of Process Engineering, Chinese Academy of Sciences Beijing China.ORCID https://orcid.org/0000-0002-6165-5487
Ai-Guo WuNingbo Key Laboratory of Biomedical Imaging Probe Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences Ningbo Zhejiang China.
Yu ShiInstitute of Pathology, Southwest Hospital Third Military Medical University Chongqing China.
Yi-Fang PingInstitute of Pathology, Southwest Hospital Third Military Medical University Chongqing China.
Jing-Hai LiState Key Laboratory of Mesoscience and Engineering, Institute of Process Engineering, Chinese Academy of Sciences Beijing China.
Xiu-Wu BianInstitute of Pathology, Southwest Hospital Third Military Medical University Chongqing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the greatest challenges in bioscience is to gain a unified view of the human immune system. This paper presents a perspective on the multilevel and multiscale complexities inherent in the immune system and discusses how these features influence the traditional research methodologies rooted in reductionism and holism. It is acknowledged that diverse complexities of the immune system are multilevel in nature, with each level showing multiscale properties, and the complexity emerging always at mesoscales in mesoregimes. Mesoscience encompasses both mesoscales, which represent the intermediate scales between the element scales and system scales at different levels, and mesoregimes, defined as transitional regimes governed by the interplay of at least two dominant mechanisms between two limiting regimes at each level. Therefore, mesoscience provides a promising paradigm to study the complexity and diversity of the immune system by bridging the gaps across multiple hierarchical levels. In particular, we focus on the mesoscience methodology to address the complexities in the immune system and offer insights into potential diagnostic, therapeutic, and theranostic strategies for immune-related diseases from a mesoscience perspective.

Indexed as

immune systemmesoregimemesoscalemesoscienceresearch paradigm

Identifiers

PMID41122466
PMCPMC12536266

What OpenQuestion holds

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LicenceCC BY
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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.