Evidence map›Paper›PMID 41857773›Full record

ArticleJournal of clinical laboratory analysis2026

Experimental Validation of an Immune Cell Infiltration Signature in Psoriasis: Translating Computational Modeling to In Vivo Efficacy.

Tingjin Zheng, Rong Xu, Jianming Zhang, Xiujuan Wen, Hao Huang, Hongfeng Tang, Zhishan Zhang, Chong Zeng

Abstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 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

8 authors.

Tingjin ZhengDepartment of Clinical Laboratory, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou City, Fujian, China.
Rong XuDepartment of Pharmacy, Quanzhou Medical College, Quanzhou City, Fujian, China.
Jianming ZhangDepartment of Clinical Laboratory, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou City, Fujian, China.
Xiujuan WenMedical Research Center & Dermatology, The Eighth Affiliated Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.
Hao HuangMedical Research Center & Dermatology, The Eighth Affiliated Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.
Hongfeng TangMedical Research Center & Dermatology, The Eighth Affiliated Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.
Zhishan ZhangDepartment of Clinical Laboratory, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou City, Fujian, China.
Chong ZengMedical Research Center & Dermatology, The Eighth Affiliated Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.ORCID https://orcid.org/0000-0002-5101-5486

Funding

National Natural Science Foundation of China 82303994The Natural Science Foundation of Fujian Province 2024J01152;2024J011538
6 · The paper itself

Abstract

objectiveThe psoriatic immune microenvironment (PIME) is central to psoriasis pathogenesis, yet its mechanistic drivers are incompletely defined. This study aimed to delineate immune cell infiltration patterns and identify pivotal disease-related immune genes through a systematic analysis of the PIME.

methodsWe evaluated the infiltration levels of 28 immune cell subtypes in 11 psoriasis-related microarray datasets using single-sample gene set enrichment analysis (ssGSEA). Subsequent differential expression, consensus clustering, and weighted gene co-expression network analysis (WGCNA) were employed to identify key genes. These findings were validated using human psoriatic tissue samples and an imiquimod-induced murine psoriasis model to construct a predictive model termed IMscore.

resultsOur analysis identified five pivotal immune-related differentially expressed genes (ImDEGs): CXCL8, CXCL9, CCL18, RGS1, and SAMSN1. A novel predictive model, IMscore, was constructed based on these ImDEGs to assess psoriasis risk. Furthermore, immune infiltration profiling and gene set enrichment analysis demonstrated that these ImDEGs are functionally associated with psoriasis-related inflammatory pathways, validating the diagnostic utility of the IMscore framework.

conclusionThese results provide new insights into the immunological mechanisms underlying psoriasis and establish a multi-gene signature with potential for improving early diagnosis and therapeutic development.

Indexed as

PsoriasisAnimalsChemokine CXCL9Chemokines, CCComputer SimulationDisease Models, AnimalGene Expression ProfilingHumansImiquimodImmunoinformaticsMiceRGS ProteinsCCL18 protein, humanChemokine CXCL9Chemokines, CCCXCL9 protein, humanImiquimodRGS Proteinsimmune cells infiltrationimmune microenvironmentinflammatorypsoriasis

Identifiers

PMID41857773
PMCPMC13107425

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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.