Diabetes mellitus is considered to be a global epidemic. The combination of genetic susceptibility and an unhealthy lifestyle is considered to be the main trigger of this metabolic disorder. Recently, there has been increased interest in the roles of gut microbiota as a new potential contributor to this epidemic. Research, in recent years, has contributed to an in-depth characterization of the human microbiome and its associations with various diseases, including metabolic diseases and diabetes mellitus. It is known that diet can change the composition of gut microbiota, but it is unclear how this, in turn, may influence metabolism. The main objective of this review is to evaluate the pathogenetic association between microbiota and diabetes and to explore any new therapeutic agents, including nutraceuticals that may modulate the microbiota. We also look at several mechanisms involved in this process. There is a clear, bidirectional relationship between microbiota and diabetes. Current treatments for diabetes influence microbiota in various ways, some beneficial, but others with still unclear effects. Microbiota-aimed treatments have seen no real-world significant effects on the progression of diabetes and its complications, with more studies needed in order to find a really beneficial agent.

Oxidative stress plays a key role in the development of chronic diabetes-related complications. Previous metabolomic studies showed a positive association of diabetes and insulin resistance with branched-chain amino acids (AAs) and aromatic AAs. The purpose of this research is to identify distinct metabolic changes associated with increased oxidative stress, as assessed by nitrotyrosine levels, in type 2 diabetes (T2DM). Serum samples of 80 patients with insulin-treated T2DM are analyzed by AA-targeted metabolomics using ultrahigh-performance liquid chromatography/mass spectrometry. Patients are divided into two groups based on their nitrotyrosine levels: the highest level of oxidative stress (Q4 nitrotyrosine) and lower levels (Q1–Q3 nitrotyrosine). The identification of biomarkers is performed in MetaboAnalyst version 5.0 using a t-test corrected for false discovery rate, unsupervised principal component analysis and supervised partial least-squares discriminant analysis (PLS-DA). Four AAs have significantly different levels between the groups for highest and lower oxidative stress. Cysteine, phenylalanine and tyrosine are substantially increased while citrulline is decreased (p-value 1). Corresponding pathways that might be disrupted in patients with high oxidative stress are phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, phenylalanine metabolism, cysteine and methionine metabolism and tyrosine metabolism.

The aim of this analysis was to assess the costs associated with the hospitalizations of persons with diabetes in a Romanian public hospital. We performed a retrospective “top-down” cost analysis of all adult patients discharged from a tertiary care hospital with an ICD-10 primary or secondary code of diabetes mellitus (type 1, type 2, or specific forms) between 1 January 2015 and 31 December 2018. All costs were adjusted with the annual inflation rates and converted to EUR. We included 16,868 patients with diabetes and 28,055 episodes of hospitalization. The total adjusted hospitalization cost in the analyzed period was EUR 26,418,126.8 and the adjusted median cost/episode of hospitalization was EUR 596.5. The mean length of a hospital stay/episode was 7.3 days. In the multivariate regression analysis, higher adjusted average costs/episodes of hospitalization and longer lengths of hospital stays were associated with increasing age, the presence of cardiovascular diseases, chronic kidney disease, and foot ulcerations. Moreover, a significant association between the average cost/episode of hospitalization and the length of hospital stay was observed (β = 0.704, p < 0.001). This study shows the burden on Romanian public hospitals of inpatient diabetes care and the main drivers of the costs.

The objective of this scoping review was to summarize previous studies which examined the effect of day-to-day variability in sleep timing and social jetlag (SJL) on dietary intake. A systematic literature search was conducted in PubMed, Embase, and Clarivate Analytics Web of Science and we identified 22 records. No difference in caloric and macronutrient intake between SJL groups was observed in studies that enrolled healthy young adults. However, studies that enrolled participants with obesity and obesity-related chronic conditions reported a higher caloric intake and a higher intake of carbohydrates, total fat, saturated fats, and cholesterol in participants with SJL than in those without. Most studies reported a lower quality of diet, a delayed mealtime, and eating jetlag in participants with SJL vs. those without SJL. No correlation of day-to-day variability in sleep timing with average caloric intake was observed, but bed-time variability was negatively associated with diet quality. Methodological issues have been identified in sources assessed including study design, power calculation, population enrolled, and tools/metrics used for sleep timing variability assessment. Future well powered longitudinal studies, with clear protocols, standardized metrics, including all age groups from general population are needed to clarify the dietary intake consequences of variability in sleep timing.