Type 2 Diabetes Mellitus (T2DM) and Carbohydrate Metabolism in Relation to T2DM from Endocrinology, Neurophysiology, Molecular Biology, and Biochemistry Perspectives

Mills, Hilla; Acquah, Ronald; Tang, Nova; Cheung, Liana; Klenk, Simon; Glassen, Katharina; Pirson, Michael; Albert, Alexandra; Hoang, Don; Vân, Trần Thị

doi:10.1155/2022/1708769

Cited by 9 publications

(10 citation statements)

References 72 publications

(100 reference statements)

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“…Hypertension and diabetes mellitus are two of the most common cardiovascular risk factors with over two thirds of the diabetic population having high blood pressure (BP) [1].The underlying pathophysiological mechanism behind the development of hypertension in patients with type 2 diabetes is thought to be related to the effect of insulin resistance on the nitric-oxide pathway, the stimulatory effect of hyperinsulinemia on the sympathetic drive, smooth muscle growth, sodium-fluid retention, and the excitatory effect of hyperglycemia on the renin-angiotensin-aldosterone system [1]. On the other hand, carbohydrates metabolism disturbance in hypertensive patients may predispose them to diabetes development [2,3], suggesting a bidirectional pathogenic relationship between hypertension and type 2 diabetes. The risk for microvascular and macrovascular complications is greatly increased when diabetes and hypertension coexist.…”

Section: Introductionmentioning

confidence: 99%

Blood pressure control and its associated factors in patients with hypertension and type 2 diabetes

et al. 2023

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In this retrospective study, the medical records of hypertensive patients with type 2 diabetes attending two major hospitals were reviewed to find the factors associated with poor blood pressure control in patients who have diabetes as a comorbid disease with hypertension. Binary regression analysis was conducted to find the factors independently associated with BP control. A total of 522 participants were included in the study. Most of the participants had uncontrolled hypertension (63.4%) and uncontrolled type 2 diabetes (51.3%). Regression results revealed that having retinopathy (OR=1.468 (95% CI: 1.020-2.113), p<0.05), and not receiving dipeptidyl-peptidase 4 (DPP4) inhibitors were independently associated with uncontrolled BP (OR=0.633 (95%CI 0.423-0.946), p<0.05). Therefore, greater efforts should be exerted to improve BP control in hypertensive patients with type 2 diabetes, particularly in those suffering from retinopathy.

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Section: Introductionmentioning

confidence: 99%

Blood pressure control and its associated factors in patients with hypertension and type 2 diabetes

et al. 2023

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“…JESS is a useful technique for treating neglected, resistant, and relapsed cases of CTEV [ 12 ]. Mathematic tools have been widely used in medical analysis [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Retrospective Case Analysis of 104 Cases of Talipes Equinus

Tan

Yang

Liu

et al. 2022

Journal of Environmental and Public Health

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A retrospective study of 104 patients (81 male and 23 females, the age range from 2 to 288days) with talipes equinus was conducted to explore the case factors associated with it. We analyzed and discussed the correlation of plaster correction times, age of first visit, gender, and birthplace of patients in the department and understood their correlation and causality. The data were analyzed using frequency analysis, normality test, chi-square goodness-of-fit test, chi-square test, and PLS regression. The findings are set out below. All the distributions of the number of plaster casts in the samples did not have normality. Therefore, we used the nonparametric test and partial least squares regression (PLS regression) and found that the number of plaster casts was more closely related to the age at first visit, gender, and birthplace and had a strong positive correlation. There was a negative correlation between the times of plaster correction and the compliance of braces. The lower the compliance of patients with braces, the more times the plaster correction will be conducted.

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“…The body’s ability to regulate blood glucose levels becomes compromised, leading to hyperglycemia. Insulin resistance and impaired insulin secretion contribute to this dysregulation [66]. Also, amino acids play essential roles in cellular metabolism and have implications for glucose homeostasis and insulin action.…”

Section: Resultsmentioning

confidence: 99%

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Matchado,

Rühlemann,

Reimeiter

et al. 2023

Preprint

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Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type 2 diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

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Type 2 Diabetes Mellitus (T2DM) and Carbohydrate Metabolism in Relation to T2DM from Endocrinology, Neurophysiology, Molecular Biology, and Biochemistry Perspectives

Cited by 9 publications

References 72 publications

Blood pressure control and its associated factors in patients with hypertension and type 2 diabetes

Blood pressure control and its associated factors in patients with hypertension and type 2 diabetes

[Retracted] Retrospective Case Analysis of 104 Cases of Talipes Equinus

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

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