Evidence map›Paper›PMID 37660146›Full record

ArticleScientific reports2023

Probing the communication patterns of different chondrocyte subtypes in osteoarthritis at the single cell level using pattern recognition and manifold learning.

Jiajian Wang, Caihong Liu, Litao Yang, Huixiong Chen, Mingqi Zheng, Yanbin Wan, Xiongxin Hong, Sidi Li, Jing Han, Ruibin Luo and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. 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
0.2field-weighted citation impact, top 39% of its field
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, 1 citations in OpenAlex.

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

13 authors at 5 institutions in 1 country.

Jiajian WangClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China. jiajianwang2019@gmail.com.
Caihong LiuSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, China.
Litao YangClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Huixiong ChenClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Mingqi ZhengClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Yanbin WanClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Xiongxin HongClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Sidi LiInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Jing HanWarshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, China.
Ruibin LuoDepartment of Clinical Laboratory, Longgang District Central Hospital of Shenzhen, Shenzhen, 518116, Guangdong, China.
Xing WanClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China.
Jian V ZhangShenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. jian.zhang@siat.ac.cn.
Ruihuan XuClinical Laboratory Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China. xrh69@126.com.
Chinese University of Hong Kong, Shenzhen · CNShenzhen University Health Science Center · CNArmy Medical University · CNLonggang Central Hospital · CNShenzhen Second People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The patterns of communication among different chondrocyte subtypes in human cartilage degeneration and regeneration help us understand the microenvironment of osteoarthritis and optimize cell-targeted therapies. Here, a single-cell transcriptome dataset of chondrocytes is used to explore the synergistic and communicative patterns of different chondrocyte subtypes. We collected 1600 chondrocytes from 10 patients with osteoarthritis and analyzed the active communication patterns for the first time based on network analysis and pattern recognition at the single-cell level. Manifold learning and quantitative contrasts were performed to analyze conserved and specific communication pathways. We found that ProCs (Proliferative chondrocytes), ECs (Effector chondrocytes), preHTCs (Prehypertrophic chondrocytes), HTCs (Hypertrophic chondrocytes), and FCs (Fibrocartilage chondrocytes) are more active in incoming and outgoing signaling patterns, which is consistent with studies on their close functional cooperation. Among them, preHTCs play multiple roles in chondrocyte communication, and ProCs and preHTCs have many overlapping pathways. These two subtypes are the most active among all chondrocyte subtypes. Interestingly, ECs and FCs are a pair of "mutually exclusive" subtypes, of which ECs are predominant in incoming patterns and FCs in outgoing patterns. The active signaling pathways of ECs and FCs largely do not overlap. COLLAGEN and LAMININ are the main pivotal pathways, which means they are very important in the repair and expansion of joint homeostasis. Notably, only preHTCs assume multiple roles (including sender, receiver, mediator, and influencer) and are involved in multiple communication pathways. We have examined their communication patterns from the perspective of cellular interactions, revealed the relationships among different chondrocyte subtypes, and, in particular, identified a number of active subtypes and pathways that are important for targeted therapy in the osteoarthritic microenvironment. Our findings provide a new research paradigm and new insights into understanding chondrocyte activity patterns in the osteoarthritic microenvironment.

Indexed as

ChondrocytesOsteoarthritisHumansHypertrophyLearning

Identifiers

PMID37660146
PMCPMC10475121
OpenAlexW4386391044

What OpenQuestion holds

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LicenceCC BY
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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.