Evidence map›Paper›PMID 35141233›Full record

ArticleFrontiers in cell and developmental biology2021

Jianlin Shen, Bowen Fu, Yanjiao Wu, Yang Yang, Xiaoning Lin, Haibin Lin, Huan Liu, Wenhua Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. 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
0.4field-weighted citation impact, top 43% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
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 at 4 institutions in 1 country.

Jianlin ShenGuangdong Innovation Platform for Translation of 3D Printing Application, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Bowen FuGuangdong Innovation Platform for Translation of 3D Printing Application, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Yanjiao WuDepartment of Orthopedics, Shunde Hospital of Southern Medical University, Guangzhou, China.
Yang YangGuangdong Engineering Research Center for Translation of Medical 3D Printing Application, Guangdong Provincial Key Laboratory of Medical Biomechanics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
Xiaoning LinDepartment of Orthopedics, Affiliated Hospital of Putian University, Putian, China.
Haibin LinDepartment of Orthopedics, Affiliated Hospital of Putian University, Putian, China.
Huan LiuDepartment of Orthopedics, Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.
Wenhua HuangGuangdong Innovation Platform for Translation of 3D Printing Application, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Putian University · CNSouthern Medical University · CNSouthwest Medical University · CNThird Affiliated Hospital of Southern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporosis is the most common metabolic bone disease in postmenopausal women. As precursors of osteoclasts, peripheral blood mononuclear cells are accessible and considered suitable models for studying osteoporosis pathology. Ubiquitination is a crucial protein degradation system in bone metabolism. The aim of this study was to identify potential ubiquitination-related genes in PBMCs that are related to osteoporosis pathogenesis. Therefore, we performed an integrated analysis of osteoporosis-related microarray datasets. With the obtained ubiquitination-related gene set, weighted gene coexpression network analysis was performed. The results showed that genes in the turquoise module were correlated with menopause, and 48 genes were identified as hub genes. A differential expression analysis revealed 43 differentially expressed genes between pre- and postmenopausal samples. After integrating the information on differentially expressed menopause-related genes, we found that several members of the ubiquitin-specific protease (

Indexed as

menopauseosteoporosisperipheral blood mononuclear cellsubiquitinationubiquitin-specific protease 25weighted gene coexpression network analysis

Identifiers

PMID35141233
PMCPMC8819182
OpenAlexW4206954471

What OpenQuestion 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 OpenQuestion graph.