Article in Mediators of inflammation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
16 authors.
Diyang KeDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0009-9014-5134
Yu WuDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0000-7089-495X
Daizai LeiDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-7001-8172
Xiaozhan ZhengDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0009-7778-5233
Ningning TangDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-5804-0369
Lingjuan LiuDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-2519-3019
Li JiangDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-5933-5396
Zhijie NiuDepartment of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China, gxmu.edu.cn.
Shaoyang ZhangDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0003-2696-5823
Wenjing HeDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.
Chaolan ShenDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0001-7398-5996
Yuanjun QinDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0003-3214-8248
Haibin ZhongDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.
Ling CuiDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-0064-627X
Fan XuDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0002-1504-2356
Fen TangDepartment of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region and Guangxi Key Laboratory of Eye Health and Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0001-9762-5231
Funding
Major Talent Program of Guangxi Zhuang Autonomous RegionNatural Science Foundation of Guangxi Province 2022GXNSFAA035495Natural Science Foundation of Guangxi Province 2025GXNSFDA069013
6 · The paper itself
Abstract
purposeDiabetic retinopathy (DR) is a leading vision-threatening disease and a common complication of diabetes. However, the understanding of how metabolic dysfunction correlates with ocular inflammation in DR remains poorly understood. Therefore, in this study, we investigated the association between these two factors in DR.
methodsUsing untargeted metabolomics analysis and mass spectrometry detection, the plasma metabolic characteristics of 27 DR patients (15 with nonproliferative diabetic retinopathy [NPDR] and 12 with proliferative diabetic retinopathy [PDR]) and 8 healthy controls (HCs) were examined. Additionally, the concentrations of inflammatory factors and vascular endothelial growth factor (VEGF) in their aqueous humor were measured. Further analysis was conducted to evaluate the correlation between metabolic disorders and abnormalities in inflammatory factors and VEGF in the aqueous humor.
resultsMetabolomic analysis revealed significant metabolic dysregulation in DR, with PDR exhibiting particularly pronounced alterations compared to NPDR and HC. ROC analysis identified creatinine, glutamine, indoleacetic acid, and methionine as reliable biomarkers for distinguishing PDR. Elevated cytokines, such as IL-6, IL-8, and VEGF, were significantly correlated with specific metabolism pathways.
conclusionOur study highlights potential biomarkers for DR stratification and provide novel insights into the link between metabolic dysfunction and ocular inflammation/ischemia in PDR.
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.