ArticleBioMed research international2013
Association of Toll-like receptor 4 polymorphisms with diabetic foot ulcers and application of artificial neural network in DFU risk assessment in type 2 diabetes patients.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantitative assessment of TLR4 gene polymorphisms and T2DM risk: A meta-analysis.Molecular genetics & genomic medicine · 2020Pooled it
- Pheochromocytoma unmasked by stress cardiomyopathy.Journal of geriatric cardiology : JGC · 2026Article
- Paeoniflorin as a candidate disease-modifying therapy for diabetic peripheral neuropathy: mechanisms, exposure challenges, and translational priorities.Frontiers in pharmacology · 2026Review
- Association of Toll-like Receptor 4 Gene Polymorphisms with Diabetes Type 2 Patients in the Palestinian Population.Endocrine, metabolic & immune disorders drug targets · 2025Article
- Analysis of immune cell activation in patients with diabetes foot ulcer from the perspective of single cell.European journal of medical research · 2024Article
- Diabetes management in the era of artificial intelligence.Archives of medical sciences. Atherosclerotic diseases · 2024Article
- Molecular Effect of Variants in Toll-like Receptor 4 Gene in Saudi Patients with Type 2 Diabetes Mellitus.Cells · 2023Article
- Association betweenDiagnostics (Basel, Switzerland) · 2023Article
- Diabetic wounds and artificial intelligence: A mini-review.World journal of clinical cases · 2023Review
- Single nucleotide variations in the development of diabetic foot ulcer: A narrative review.World journal of diabetes · 2022Review
- Artificial Intelligence Methodologies Applied to Technologies for Screening, Diagnosis and Care of the Diabetic Foot: A Narrative Review.Biosensors · 2022Review
- Individualised screening of diabetic foot: creation of a prediction model based on penalised regression and assessment of theoretical efficacy.Diabetologia · 2022Article
- Machine learning in vascular surgery: a systematic review and critical appraisal.NPJ digital medicine · 2022Review
- Epigenetic basis of diabetic vasculopathy.Frontiers in endocrinology · 2022Review
- TLR4 gene polymorphisms in Egyptian vitiligo patients: insights into emerging association with clinical activity, family history, and response to therapy.Journal, genetic engineering & biotechnology · 2021Article
- The Immune Functions of Keratinocytes in Skin Wound Healing.International journal of molecular sciences · 2020Review
- The Role of Poly(ADP-Ribose) Polymerase-1 in Cutaneous Wound Healing.Advances in wound care · 2019Review
- Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods.Healthcare informatics research · 2019Review
- Haplotype analysis ofThe Indian journal of medical research · 2019Article
- Toll-like receptor 4 polymorphisms in Saudi population with cardiovascular diseases.Molecular genetics & genomic medicine · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Toll-Like receptor 4 (TLR4) plays an important role in immunity, tissue repair, and regeneration. The objective of the present work was to evaluate the association of TLR4 single nucleotide polymorphisms (SNPs) rs4986790, rs4986791, rs11536858 (merged into rs10759931), rs1927911, and rs1927914 with increased diabetic foot ulcer (DFU) risk in patients with type 2 diabetes mellitus (T2DM). PCR-RFLP was used for genotyping TLR4 SNPs in 125 T2DM patients with DFU and 130 controls. The haplotypes and linkage disequilibrium between the SNPs were determined using Haploview software. Multivariate linear regression (MLR) and artificial neural network (ANN) modeling was done to observe their predictability for the risk of DFU in T2DM patients. Risk genotypes of all SNPs except rs1927914 were significantly associated with DFU. Haplotype ACATC (P value = 9.3E - 5) showed strong association with DFU risk. Two haplotypes ATATC (P value = 0.0119) and ATGTT (P value = 0.0087) were found to be protective against DFU. In conclusion TLR4 SNPs and their haplotypes may increase the risk of impairment of wound healing in T2DM patients. ANN model (83%) is found to be better than the MLR model (76%) and can be used as a tool for the DFU risk assessment in T2DM patients.
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