Evidence map›Paper›PMID 42136146›Full record

ArticleJournal of clinical laboratory analysis2026

COL1A1

Chengzi Tian, Zaiyi Li

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

2 authors.

Chengzi TianDepartment of Gynecology, the First People's Hospital of Yunnan Province, Kunming University of Science and Technology Affiliated Hospital, Kunming, China.
Zaiyi LiDepartment of Obstetrics and Gynecology, Reproductive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China.ORCID https://orcid.org/0000-0002-7373-9901

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndometritis is linked to adverse reproductive outcomes, but epithelial programs in disease initiation and persistence remain unclear. We aimed to systematically define inflammation-associated epithelial states and regulation in endometritis using single-cell analysis.

methodThe single-cell RNA sequencing (scRNA-seq) data from Gene Expression Omnibus (GEO) were processed using Seurat. After quality control, data were normalized with SCTransform and batch-corrected using the Harmony package. Cell types were annotated based on canonical markers. Differential expression analysis was performed to identify genes altered in endometritis. Epithelial cells were subsetted for reclustering and trajectory inference using Monocle2. Cell-cell communication was inferred with CellChat, and transcriptional regulon activity was assessed using SCENIC and AUCell methods.

resultsA total of 153,877 cells formed 14 clusters across seven lineages, with lower epithelial proportion in endometritis. Epithelial cells included four subpopulations (SPDEF

conclusionThis epithelial-centric single-cell atlas delineates disease-associated states, fate decisions, signaling axes, and regulatory programs in endometritis. The data support a model of epithelial fate remodeling coupled to angiogenic signaling and AP-1-driven transcription, nominating testable targets for mechanistic validation and potential translation.

Indexed as

cell–cell communicationendometritisepithelial heterogeneitypseudotimesingle‐cell RNA‐seq

Identifiers

PMID42136146
PMCPMC13399849

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.