Inflammation, oxidative stress and mitochondrial dysfunction in the progression of type II diabetes mellitus with coexisting hypertension

IntroductionType II diabetes mellitus (T2DM) is a metabolic disorder that poses a serious health concern worldwide due to its rising prevalence. Hypertension (HT) is a frequent comorbidity of T2DM, with the co-occurrence of both conditions increasing the risk of diabetes-associated complications. Inflammation and oxidative stress (OS) have been identified as leading factors in the development and progression of both T2DM and HT. However, OS and inflammation processes associated with these two comorbidities are not fully understood. This study aimed to explore changes in the levels of plasma and urinary inflammatory and OS biomarkers, along with mitochondrial OS biomarkers connected to mitochondrial dysfunction (MitD). These markers may provide a more comprehensive perspective associated with disease progression from no diabetes, and prediabetes, to T2DM coexisting with HT in a cohort of patients attending a diabetes health clinic in Australia.MethodsThree-hundred and eighty-four participants were divided into four groups according to disease status: 210 healthy controls, 55 prediabetic patients, 32 T2DM, and 87 patients with T2DM and HT (T2DM+HT). Kruskal-Wallis and χ2 tests were conducted between the four groups to detect significant differences for numerical and categorical variables, respectively.Results and discussionFor the transition from prediabetes to T2DM, interleukin-10 (IL-10), C-reactive protein (CRP), 8-hydroxy-2’-deoxyguanosine (8-OHdG), humanin (HN), and p66Shc were the most discriminatory biomarkers, generally displaying elevated levels of inflammation and OS in T2DM, in addition to disrupted mitochondrial function as revealed by p66Shc and HN. Disease progression from T2DM to T2DM+HT indicated lower levels of inflammation and OS as revealed through IL-10, interleukin-6 (IL-6), interleukin-1β (IL-1β), 8-OHdG and oxidized glutathione (GSSG) levels, most likely due to antihypertensive medication use in the T2DM +HT patient group. The results also indicated better mitochondrial function in this group as shown through higher HN and lower p66Shc levels, which can also be attributed to medication use. However, monocyte chemoattractant protein-1 (MCP-1) levels appeared to be independent of medication, providing an effective biomarker even in the presence of medication use. The results of this study suggest that a more comprehensive review of inflammation and OS biomarkers is more effective in discriminating between the stages of T2DM progression in the presence or absence of HT. Our results further indicate the usefulness of medication use, especially with respect to the known involvement of inflammation and OS in disease progression, highlighting specific biomarkers during disease progression and therefore allowing a more targeted individualized treatment plan

Empirical investigation of decision tree ensembles for monitoring cardiac complications of diabetes

Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature

Effect of GABA-Fortified Oolong Tea on Reducing Stress in a University Student Cohort

GABA-containing tea has gained popularity as an accessible intervention to reduce the impact of chronic stress-induced autonomic imbalance and increased risk for cardiovascular disease despite a lack of evidence concerning the γ-aminobutyric acid (GABA) content in a cup of the tea and its effects on physiological and psychological stress as measures of cognitive function. We aimed to measure the effects of GABA-fortified tea consumption on heart rate variability (HRV) and stress in 30 participants using a pre-post cohort study design. Ten minute lead II ECG recordings were analyzed with Kubios software. Frequency domain parameters including total power, high and low frequency power, along with heart rate, were determined. A control group that consumed a non-fortified tea was included in the research. Statistical analysis was by two-way ANOVA for two-group comparison with time as an interaction and a significance level of p < 0.05. Oolong tea consumption led to a significant decrease in the immediate stress score and a significant improvement in HRV. We conclude that autonomic imbalance and HRV in people with acute stress is significantly reduced following a cup of GABA fortified oolong tea and highlights the complex interaction between autonomic nervous system function and mood

Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification

We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or non-vessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and continuous two-dimensional Morlet wavelet transform responses taken at multiple scales. The Morlet wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces and compare its performance with the linear minimum squared error classifier. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE and STARE databases of manually labeled non-mydriatic images. On the DRIVE database, it achieves an area under the receiver operating characteristic (ROC) curve of 0.9598, being slightly superior than that presented by the method of Staal et al.Comment: 9 pages, 7 figures and 1 table. Accepted for publication in IEEE Trans Med Imag; added copyright notic

Heart Rate Variability and QT Dispersion in a Cohort of Diabetes Patients

Abstrac

Automated detection of proliferative retinopathy in clinical practice

Timely intervention for diabetic retinopathy (DR) lessens the possibility of blindness and can save considerable costs to health systems. To ensure that interventions are timely and effective requires methods of screening and monitoring pathological changes, including assessing outcomes. Fractal analysis, one method that has been studied for assessing DR, is potentially relevant in today’s world of telemedicine because it provides objective indices from digital images of complex patterns such as are seen in retinal vasculature, which is affected in DR. We introduce here a protocol to distinguish between nonproliferative (NPDR) and proliferative (PDR) changes in retinal vasculature using a fractal analysis method known as local connected dimension (Dconn) analysis. The major finding is that compared to other fractal analysis methods, Dconn analysis better differentiates NPDR from PDR (p = 0.05). In addition, we are the first to show that fractal analysis can be used to differentiate between NPDR and PDR using automated vessel identification. Overall, our results suggest this protocol can complement existing methods by including an automated and objective measure obtainable at a lower level of expertise that experts can then use in screening for and monitoring DR

Effects of Kinesiology Tape on Non-linear Center of Mass Dispersion During the Y Balance Test

Static taping of the ankle or knee joint is a common method of reducing risk of injury by providing mechanical stability. An alternative taping technique employs kinesiology tape, which has the additional benefit of improving functionality by stimulating proprioception. There is substantial disagreement whether kinesiology tape shows significant differences in proprioception and postural stability as compared to rigid/static tape when applied at the lower limb. The current study investigated the effects of kinesiology tape and static tape during a Y Balance Test on center of mass as an indicator for postural stability. Forty-one individuals, free of injury, performed the Y Balance Test under the three conditions; no tape, kinesiology tape, and static tape applied at the lower limb to the quadriceps, triceps surae and ankle joint. All participants completed the Y Balance Test to determine whether any significant differences could be observed using center of mass movement as a surrogate measure for balance and proprioception. The Minkowski-Bouligand and box-counting fractal dimension analyses were used as measures of the dynamic changes in the center of mass whilst undertaking the Y Balance Test. Statistical analyses included the Kruskal Wallis test to allow for non-normally distributed data and a Bonferroni corrected pairwise T-test as a post hoc test to ascertain pairwise differences between the three taping conditions. Significance was set at 0.05. The fractal analyses of the dynamic changes in center of mass showed significant differences between the control and both the static tape and kinesiology tape groups (p = 0.021 and 0.009, respectively). The current study developed a novel measure of dynamic changes in the center of mass during a set movement that indicated real-time processing effects during a balance task associated with the type of taping used to enhance postural stability

Increased markers of cardiac vagal activity in leucine-rich repeat kinase 2-associated Parkinson's disease.

PurposeCardiac autonomic dysfunction manifests as reduced heart rate variability (HRV) in idiopathic Parkinson's disease (PD), but no significant reduction has been found in PD patients who carry the LRRK2 mutation. Novel HRV features have not been investigated in these individuals. We aimed to assess cardiac autonomic modulation through standard and novel approaches to HRV analysis in individuals who carry the LRRK2 G2019S mutation.MethodsShort-term electrocardiograms were recorded in 14 LRRK2-associated PD patients, 25 LRRK2-non-manifesting carriers, 32 related non-carriers, 20 idiopathic PD patients, and 27 healthy controls. HRV measures were compared using regression modeling, controlling for age, sex, mean heart rate, and disease duration. Discriminant analysis highlighted the feature combination that best distinguished LRRK2-associated PD from controls.ResultsBeat-to-beat and global HRV measures were significantly increased in LRRK2-associated PD patients compared with controls (e.g., deceleration capacity of heart rate: p = 0.006) and idiopathic PD patients (e.g., 8th standardized moment of the interbeat interval distribution: p = 0.0003), respectively. LRRK2-associated PD patients also showed significantly increased irregularity of heart rate dynamics, as quantified by Rényi entropy, when compared with controls (p = 0.002) and idiopathic PD patients (p = 0.0004). Ordinal pattern statistics permitted the identification of LRRK2-associated PD individuals with 93% sensitivity and 93% specificity. Consistent results were found in a subgroup of LRRK2-non-manifesting carriers when compared with controls.ConclusionsIncreased beat-to-beat HRV in LRRK2 G2019S mutation carriers compared with controls and idiopathic PD patients may indicate augmented cardiac autonomic cholinergic activity, suggesting early impairment of central vagal feedback loops in LRRK2-associated PD

Genetic studies of metabolic syndrome in Arab populations: A systematic review and meta-analysis

Background: The metabolic syndrome (MetS) is prevalent in Arabian populations. Several small-scale studies have been performed to investigate the genetic basis of MetS. This systematic review and meta-analysis aimed to examine whether candidate gene polymorphisms are associated with MetS susceptibility among ethnic groups of the Arabian world and to suggest possible directions for future research regarding genetic markers and MetS. Methods: A search was conducted for peer-reviewed articles that examined the genetic association of MetS in Arabian populations in the following databases: Medline, Embase, Scopus, Direct Science, Web of Science, ProQuest, and Google Scholar until March 31, 2021. Articles were eligible if they were case-control studies, which investigated MetS as a dichotomous outcome (MetS vs no MetS). To assess the quality of the studies, the Q-Genie tool (Quality of Genetic Association Studies) was used. A non-central chi2 (random-effect) distribution was used to determine the heterogeneity (H) of Q and I (Galassi et al., The American journal of medicine, 2006, 119, 812–819) statistics. Results: Our search strategy identified 36 studies that met our inclusion criteria. In most cases, studies were excluded due to a lack of statistical information such as odds ratios, confidence intervals, and p-values. According to the Q-Genie tool, 12 studies scored poorly (a score of ≤ 35), 13 studies scored moderately ( \u3e 35 and ≤ 45), and 12 studies had good quality ( \u3e 45 or higher). The most frequently studied genes were FTO and VDR (both included in four studies). Three SNPs indicated increased risk for MetS after calculating the pooled odds ratios: FTO-rs9939609 (odds ratio 1.49, 95% CI: 0.96–2.32); LEP-rs7799039 (odds ratio 1.85, 95% CI: 1.37–2.5); and SERPINA12-rs2236242 (odds ratio 1.65, 95% CI: 1.21–2.24). Meta-analysis studies showed no significant heterogeneity. Conclusion: There were many sources of heterogeneity in the study settings. Most of the studies had low to moderate quality because of sample size and power issues, not considering all potential sources of bias, and not providing details about genotyping methods and results. As most studies were small-scale, aimed to replicate findings from other populations, we did not find any unique genetic association between MetS and Arabian populations