Skin tissue repair is of fundamental importance for maintaining homeostasis regulation, protection barrier, absorption, and excretion of skin tissue. Wound healing is a complicated process that can be impaired by infections and therefore have a significant economic and social impact. Simultaneously, the overuse of antibiotics has led to antimicrobial resistance and loss of their efficacy. Thus, the need for alternative antimicrobial agents is urgent. The newest approaches on wound dressings employ new therapeutic agents, such as probiotics. Probiotics alone or in tandem with nanotechnology-based techniques exhibit a broad range of benefits on surgical wounds. This systematic review aims to consider current knowledge of probiotic effects on animals and humans regarding surgical wound healing and provide new insights into the role of nanotechnology. The databases included were PubMed (MEDLINE), Scopus, and Cochrane Library (CENTRAL). Studies focused on burns, chronic wounds, and diabetic ulcers were excluded. The promising industry of probiotics demonstrates a significant upsurge as more and more healthy individuals rely their well-being on alternative medicine. Included probiotics illustrated positive results on wound re-epithelization, neovascularization, and wound healing. No adverse effects were noted.

Atrial fibrillation (AF) and diabetes mellitus (DM) constitute two major closely inter-related chronic cardiovascular disorders whose concurrent prevalence rates are steadily increasing. Although, the pathogenic mechanisms behind the AF and DM comorbidity are still vague, it is now clear that DM precipitates AF occurrence. DM also affects the clinical course of established AF; it is associated with significant increase in the incidence of stroke, AF recurrence, and cardiovascular mortality. The impact of DM on AF management and prognosis has been adequately investigated. However, evidence on the relative impact of glycemic control using glycated hemoglobin levels is scarce. This review assesses up-to-date literature on the association between DM and AF. It also highlights the usefulness of glycated hemoglobin measurement for the prediction of AF and AF-related adverse events. Additionally, this review evaluates current anti-hyperglycemic treatment in the context of AF, and discusses AF-related decision-making in comorbid DM. Finally, it quotes significant remaining questions and sets some future strategies with the potential to effectively deal with this prevalent comorbidity.

Background Diabetes mellitus (DM) and coronary artery disease (CAD) constitute inter-related clinical entities. Biomarker profiling emerges as a promising tool for the early diagnosis and risk stratification of either DM or CAD. However, studies assessing the predictive capacity of novel metabolomics biomarkers in coexistent CAD and DM are scarce. Methods This post-hoc analysis of the CorLipid trial (NCT04580173) included 316 patients with CAD and comorbid DM who underwent emergency or elective coronary angiography due to acute or chronic coronary syndrome. Cox regression analyses were performed to identify metabolomic predictors of the primary outcome, which was defined as the composite of major adverse cardiovascular or cerebrovascular events (MACCE: cardiovascular death, myocardial infarction, stroke, major bleeding), repeat unplanned revascularizations and cardiovascular hospitalizations. Linear regression analyses were also performed to detect significant predictors of CAD complexity, as assessed by the SYNTAX score. Results After a median 2-year follow up period (IQR = 0.7 years), the primary outcome occurred in 69 (21.8%) of patients. Acylcarnitine ratio C4/C18:2, apolipoprotein (apo) B, history of heart failure (HF), age > 65 years and presence of acute coronary syndrome were independent predictors of the primary outcome in diabetic patients with CAD (aHR = 1.89 [1.09, 3.29]; 1.02 [1.01, 1.04]; 1.28 [1.01, 1.41]; 1.04 [1.01, 1.05]; and 1.12 [1.05–1.21], respectively). Higher levels of ceramide ratio C24:1/C24:0, acylcarnitine ratio C4/C18:2, age > 65 and peripheral artery disease were independent predictors of higher CAD complexity (adjusted β = 7.36 [5.74, 20.47]; 3.02 [0.09 to 6.06]; 3.02 [0.09, 6.06], respectively), while higher levels of apoA1 were independent predictors of lower complexity (adjusted β= − 0.65 [− 1.31, − 0.02]). Conclusions In patients with comorbid DM and CAD, novel metabolomic biomarkers and metabolomics-based prediction models could be recruited to predict clinical outcomes and assess the complexity of CAD, thereby enabling the integration of personalized medicine into routine clinical practice. These associations should be interpreted taking into account the observational nature of this study, and thus, larger trials are needed to confirm its results and validate them in different and larger diabetic populations.