Background: No currently available biomarkers or treatment regimens fully meet therapeutic needs of type 1 diabetes mellitus (T1DM). Circular RNA (circRNA) is a recently identified class of stable noncoding RNA that have been documented as potential biomarkers for various diseases. Our objective was to identify and analyze plasma circRNAs altered in T1DM. Methods: We used microarray to screen differentially expressed plasma circRNAs in patients with new onset T1DM (n=3) and age-/gender-matched healthy controls (n=3). Then, we selected six candidates with highest fold-change and validated them by quantitative real-time polymerase chain reaction in independent human cohort samples (n=12). Bioinformatic tools were adopted to predict putative microRNAs (miRNAs) sponged by these validated circRNAs and their downstream messenger RNAs (mRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to gain further insights into T1DM pathogenesis. Results: We identified 68 differentially expressed circRNAs, with 61 and seven being up- and downregulated respectively. Four of the six selected candidates were successfully validated. Curations of their predicted interacting miRNAs revealed critical roles in inflammation and pathogenesis of autoimmune disorders. Functional relations were visualized by a circRNA-miRNA-mRNA network. GO and KEGG analyses identified multiple inflammation-related processes that could be potentially associated with T1DM pathogenesis, including cytokine-cytokine receptor interaction, inflammatory mediator regulation of transient receptor potential channels and leukocyte activation involved in immune response. Conclusion Our study report, for the first time, a profile of differentially expressed plasma circRNAs in new onset T1DM. Further in silico annotations and bioinformatics analyses supported future application of circRNAs as novel biomarkers of T1DM.

No currently available biomarkers or treatment regimens fully meet therapeutic needs of type 1 diabetes mellitus (T1DM). Circular RNA (circRNA) is a recently identified class of stable noncoding RNA that have been documented as potential biomarkers for various diseases. Our objective was to identify and analyze plasma circRNAs altered in T1DM.

ObjectiveTo evaluate the Chinese guidelines and consensus of rehabilitation medicine published in the medical journals in 2022 using Scientific, Transparent and Applicable Rankings (STAR). MethodsGuidelines and consensus which were developed by Chinese institutions or led by Chinese scholars were retrieved in databases of CNKI, Wanfang Data, CBM, Chinese Medical Journal Network, PubMed and Web of Science, in 2022, followed by screening for rehabilitation medicine field. The literature were rated with STAR. ResultsSeven guidelines and eleven consensuses were included. The STAR scores ranged from 11.7 to 69.6, with a median score of 25.9 and mean score of 28.3. There was a significant difference in the total score between guidelines and consensus (U = 12.000, P = 0.014). The score ratio was high in the domains of recommendations (73.6%), evidence (39.5%) and others (33.3%), while it was low in the domains of protocol (1.4%), clinical questions (12.5%) and conflicts of interest (13.9%). The score ratio was high in the items of listing the institutional affiliations of all individuals involved in developing the guideline (94.4%), identifying the references for evidence supporting the main recommendations (94.4%), indicating the considerations (e.g., adverse effects) in clinical practice when implementing the recommendations (88.9%), and making the recommendations clearly identifiable, e.g., in a table, or using enlarged or bold fonts (75%); and it was low in the items of describing the role of funder(s) in the guideline development (0), indicating information about the evaluation and management of conflicts of interest (0), providing tailored editions of the guidelines for different groups of target users (0), presenting the guideline or recommendations visually, such as with figures or videos (0), providing details of the guideline protocol (2.8%), assessing the risk of bias or methodological quality of the included studies (2.8%), describing the responsibilities of all individuals or sub-groups involved in developing the guideline (5.6%), indicating how the clinical questions were selected and sorted (5.6%), formating clinical questions in PICO or other formats (5.6%), making the guideline accessible through multiple platforms (5.6%), and declaring that the funder(s) did not influence the guideline's recommendations (8.3%). ConclusionThe quality of current clinical practice guidelines and consensus of rehabilitation medicine is poor, which should be developed in accordance with the relevant standards.