Physical activity as a proxy to ameliorate inflammation in patients with type 2 diabetes and periodontal disease at high cardiovascular risk

While the beneficial impact of physical activity has been ascertained in a variety of pathological scenarios, including diabetes and low-grade systemic inflammation, its potential remains still putative for periodontal health. Periodontal disease has been associated with inflammatory systemic alterations, which share a common denominator with type 2 diabetes mellitus and cardiovascular disease. Physical exercise, along with nutritional counseling, is a cornerstone in the treatment and prevention of type 2 diabetes, also able to reduce the prevalence of periodontal disease and cardiovascular risk. In addition, considering the higher incidence of periodontitis in patients with type 2 diabetes compared to healthy controls, the fascinating research question would be whether physical activity could relieve the inflammatory pressure exerted by the combination of these two diseases. This multi-disciplinary viewpoint discusses available literature in order to argument the hypothesis of a “three–way relationship” linking diabetes, periodontitis, and physical activity.     

Circulating CCL20: A potential biomarker for active vitiligo together with the number of Th1/17 cells

Background

Vitiligo is an autoimmune disease with varying pathological features. Activation of the CCL20-CCR6 axis plays an important role in chronic inflammatory diseases. However, whether CCL20-CCR6 and Th1/17 cells are indicative of active vitiligo is unclear.

Health Care Utilization After Ventricular Tachycardia Ablation: A Propensity Score-Matched Cohort Study

Background

Catheter ablation of ventricular tachycardia (VT) can reduce the burden of ventricular arrhythmia (VA) but its effect on health care utilization and costs after such therapy is poorly known. We sought to compare the rates of cardiovascular (CV)-related hospitalizations, survival, and health care costs in patients with recurrent VT treated either with VT ablation or with medical therapy.

Colitis following the use of immune checkpoint inhibitors: A real-world analysis of spontaneous reports submitted to the FDA adverse event reporting system

BackgroundAlthough colitis has been reported in patients treated with immune checkpoint inhibitors (ICIs), associations between colitis and ICIs had not been thoroughly assessed in real-world studies. Here, we identified and characterized significant colitis-associated with ICIs.MethodsBased on the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 2004 to December 2019, the disproportionality analysis and Bayesian analysis, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN) and the multi-item gamma Poisson shrinker (MGPS) algorithms were adopted to data mining of the suspected adverse events of colitis after ICIs administrating. Clinical characteristics of patients with ICIs-associated colitis and the time to onset of colitis following different ICI regimens were collected.ResultsA total of 3786 reports of colitis adverse events were identified with ICIs. Seven ICI monotherapies were associated with the reporting of colitis. Statistically significant ROR, PRR, information component (IC), and empirical Bayesian geometric mean (EBGM) emerged for all ICI monotherapies and combination therapies. ICIs-associated colitis affected mostly male (53.51%), with a wide mean age range (60.65 to 72 years). Colitis adverse events were commonly reported in patients with melanoma and lung cancer. Adverse outcomes of colitis concerning ICI were mainly outcomes of hospitalization-initiated or prolonged and other serious. Among colitis cases, 17.43% cases of colitis concerning ICI lead to death. The adverse event of colitis occurred earliest in ipilimumab monotherapy with a median time to onset of 64.21 days (IQR: 27–69 days) among all monotherapies.ConclusionsICI may lead to severe and disabling ICIs-associated colitis during therapy. Analysis of FAERS data identified signals for adverse events of colitis with ICI regimens. Practitioners should consider the factors that may increase the likelihood of colitis. The findings support a continued surveillance and risk factor identification studies.     

Does obesity put your brain at risk?

Background and aimsThe negative impact of obesity on the brain is an issue of increasing clinical interest. Hence, this review summarized evidence linking obesity with brain morphology (gray and white matter volume), brain function (functional activation and connectivity), and cognitive function.MethodsA criticals review of the relevant published English articles between 2008 and 2022, using PubMed, Google Scholar and Science Direct. Studies were included if (1) an experimental/intervention study was conducted (2) the experiment/intervention included both high fat diet or body weight, whether it could counteract the negative effect brain morphological or functional change. Critical analysis for a supporting study was also carried out.ResultsBrain dysfunction can be recognized as result from neuroinflammation, oxidative stress, change in gut-brain hormonal functionality decrease regional blood flow or diminished hippocampal size and change in gut-brain hormonal functionality; which collectively translate into a cycle of deranged metabolic control and cognitive deficits, often obesity referred as changes in brain biochemistry and brain function. Recently, a few changes in brain structure and functions could be traced back even to obese children or adult. Evidence here suggested that obesity elicits early neuroinflammation effects, which likely disrupt the normal metabolism in hypothalamus, and hippocampus result from brain insulin resistance. The mechanisms of these robust effects are discussed herein.ConclusionBrain disease is inseparable from obesity itself and requires a better recognition to allow future therapeutic targeting for treatment of obesity. Additional research is needed to identify the best treatment targets and to identify if these changes reversible.