Diabetes mellitus: an overview of the types, symptoms, complications and management

Cloete, Linda

doi:10.7748/ns.2021.e11709

Cited by 149 publications

(88 citation statements)

References 35 publications

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“…Clinical features and laboratory findings of DM include changes in body weight, increased blood glucose, insulin resistance, development of lipid metabolism disorder, polyuria, polydipsia, visual disturbances, ketoacidosis, and hyperosmolar non-ketoacidotic syndrome with risk of coma[ 8 , 9 ]. When uncontrolled, diabetes can induce grave complications, including death[ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Potential role of Limosilactobacillus fermentum as a probiotic with anti-diabetic properties: A review

Lacerda¹,

Costa²,

Pontes³

et al. 2022

WJD

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Oxidative stress, inflammation, and gut microbiota impairments have been implicated in the development and maintenance of diabetes mellitus. Strategies capable of recovering the community of commensal gut microbiota and controlling diabetes mellitus have increased in recent years. Some lactobacilli strains have an antioxidant and anti-inflammatory system capable of protecting against oxidative stress, inflammation, and diabetes mellitus. Experimental studies and some clinical trials have demonstrated that Limosilactobacillus fermentum strains can beneficially modulate the host antioxidant and anti-inflammatory system, resulting in the amelioration of glucose homeostasis in diabetic conditions. This review presents and discusses the currently available studies on the identification of Limosilactobacillus fermentum strains with anti-diabetic properties, their sources, range of dosage, and the intervention time in experiments with animals and clinical trials. This review strives to serve as a relevant and well-cataloged reference of Limosilactobacillus fermentum strains capable of inducing anti-diabetic effects and promoting health benefits.

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Section: Introductionmentioning

confidence: 99%

Potential role of Limosilactobacillus fermentum as a probiotic with anti-diabetic properties: A review

Lacerda¹,

Costa²,

Pontes³

et al. 2022

WJD

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show abstract

“…With the development of economy and the change of life style, diabetes has gradually become a common metabolic disease [ 1 ]. As one of the chronic complications of diabetes, Diabetes Peripheral Neuropathy (DPN) is a serious threat to human life.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Lidocaine Ameliorates Diabetic Peripheral Neuropathy in Streptozotocin‐Induced Diabetic Rats through Modulating the c‐Jun Signaling Pathway

Luo

Wu²,

Wu³

et al. 2022

Contrast Media & Molecular Imaging

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As one of the common complications of diabetes mellitus (DM), Diabetic Peripheral Neuropathy (DPN) threatens human lives seriously. Emerging evidences have confirmed the protective effects of lidocaine on DPN. However, the possible role and underlying mechanisms of lidocaine in DPN have not been clarified. In this study, the potential role of lidocaine in DPN is explored, and the possible mechanisms are investigated. The rat DPN model is constructed through administration of streptozotocin (STZ, 60 mg/kg). All rats are randomly divided into four groups, including the control group, DPN group, lidocaine (3.78 mg/time) group, and lidocaine combined with the SP600125 (15 mg/kg) group. Mechanical threshold, thermal latency, and blood glucose of rats before and after treatment are detected, and Nerve Conduction Velocity (NCV) is assessed. Moreover, qRT-PCR and western blot assays are carried out to determine the expressions of the c-Jun signaling pathway. The experimental results demonstrate that lidocaine remarkably downregulates the mRNA and protein expressions of the c-Jun signaling pathway in serum and DRGs induced with DPN. Besides, lidocaine combined with SP600125 can obtain better effects than lidocaine alone. It is clearly evident that lidocaine has a certain therapeutic effect on DPN.

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“…Diabetes mellitus (DM) is one of the top three major chronic noncommunicable diseases [1]. Over 90% of DM cases are those of type 2 diabetes.…”

Section: Introductionmentioning

confidence: 99%

Identification of Type 2 Diabetes Based on a Ten‐Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm

Ding

Zhi

et al. 2022

BioMed Research International

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Background. Type 2 diabetes is a major health concern worldwide. The present study is aimed at discovering effective biomarkers for an efficient diagnosis of type 2 diabetes. Methods. Differentially expressed genes (DEGs) between type 2 diabetes patients and normal controls were identified by analyses of integrated microarray data obtained from the Gene Expression Omnibus database using the Limma package. Functional analysis of genes was performed using the R software package clusterProfiler. Analyses of protein-protein interaction (PPI) performed using Cytoscape with the CytoHubba plugin were used to determine the most sensitive diagnostic gene biomarkers for type 2 diabetes in our study. The support vector machine (SVM) classification model was used to validate the gene biomarkers used for the diagnosis of type 2 diabetes. Results. GSE164416 dataset analysis revealed 499 genes that were differentially expressed between type 2 diabetes patients and normal controls, and these DEGs were found to be enriched in the regulation of the immune effector pathway, type 1 diabetes mellitus, and fatty acid degradation. PPI analysis data showed that five MCODE clusters could be considered as clinically significant modules and that 10 genes (IL1B, ITGB2, ITGAX, COL1A1, CSF1, CXCL12, SPP1, FN1, C3, and MMP2) were identified as “real” hub genes in the PPI network using algorithms such as Degree, MNC, and Closeness. The sensitivity and specificity of the SVM model for identifying patients with type 2 diabetes were 100%, with an area under the curve of 1 in the training as well as the validation dataset. Conclusion. Our results indicate that the SVM-based model developed by us can facilitate accurate diagnosis of type 2 diabetes.

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Diabetes mellitus: an overview of the types, symptoms, complications and management

Cited by 149 publications

References 35 publications

Potential role of Limosilactobacillus fermentum as a probiotic with anti-diabetic properties: A review

Potential role of Limosilactobacillus fermentum as a probiotic with anti-diabetic properties: A review

[Retracted] Lidocaine Ameliorates Diabetic Peripheral Neuropathy in Streptozotocin‐Induced Diabetic Rats through Modulating the c‐Jun Signaling Pathway

Identification of Type 2 Diabetes Based on a Ten‐Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm

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