Effects of Short Term Adiponectin Receptor Agonism on Cardiac Function and Energetics in Diabetic db/db Mice

AdipoRon reduces TGFβ1-mediated collagen deposition in vitro and alleviates knee stiffness in vivo

Arthrofibrosis, which causes joint motion restrictions, is a common complication following total knee arthroplasty (TKA). Key features associated with arthrofibrosis include myofibroblast activation, knee stiffness, and excessive scar tissue formation. We previously demonstrated that adiponectin levels are suppressed within the knee tissues of patients affected by arthrofibrosis and showed that AdipoRon, an adiponectin receptor agonist, exhibited anti-fibrotic properties in human mesenchymal stem cells. In this study, the therapeutic potential of AdipoRon was evaluated on TGFβ1-mediated myofibroblast differentiation of primary human knee fibroblasts and in a mouse model of knee stiffness. Picrosirius red staining revealed that AdipoRon reduced TGFβ1-induced collagen deposition in primary knee fibroblasts derived from patients undergoing primary TKA and revision TKA for arthrofibrosis. AdipoRon also reduced mRNA and protein levels of ACTA2, a key myofibroblast marker. RNA-seq analysis corroborated the anti-myofibrogenic effects of AdipoRon. In our knee stiffness mouse model, 6 weeks of knee immobilization, to induce a knee contracture, in conjunction with daily vehicle (DMSO) or AdipoRon (1, 5, and 25 mg/kg) via intraperitoneal injections were well tolerated based on animal behavior and weight measurements. Biomechanical testing demonstrated that passive extension angles (PEAs) of experimental knees were similar between vehicle and AdipoRon treatment groups in mice evaluated immediately following immobilization. Interestingly, relative to vehicle-treated mice, 5 mg/kg AdipoRon therapy improved the PEA of the experimental knees in mice that underwent 4 weeks of knee remobilization following the immobilization and therapy. Together, these studies revealed that AdipoRon may be an effective therapeutic modality for arthrofibrosis.

Adiponectin as a therapeutic target for diabetic foot ulcer

The global burden of diabetic foot ulcers (DFUs) is a significant public health concern, affecting millions of people worldwide. These wounds cause considerable suffering and have a high economic cost. Therefore, there is a need for effective strategies to prevent and treat DFUs. One promising therapeutic approach is the use of adiponectin, a hormone primarily produced and secreted by adipose tissue. Adiponectin has demonstrated anti-inflammatory and anti-atherogenic properties, and researchers have suggested its potential therapeutic applications in the treatment of DFUs. Studies have indicated that adiponectin can inhibit the production of pro-inflammatory cytokines, increase the production of vascular endothelial growth factor, a key mediator of angiogenesis, and inhibit the activation of the intrinsic apoptotic pathway. Additionally, adiponectin has been found to possess antioxidant properties and impact glucose metabolism, the immune system, extracellular matrix remodeling, and nerve function. The objective of this review is to summarize the current state of research on the potential role of adiponectin in the treatment of DFUs and to identify areas where further research is needed in order to fully understand the effects of adiponectin on DFUs and to establish its safety and efficacy as a treatment for DFUs in the clinical setting. This will provide a deeper understanding of the underlying mechanisms of DFUs that can aid in the development of new and more effective treatment strategies.

Are Only p-Values Less Than 0.05 Significant? A p-Value Greater Than 0.05 Is Also Significant!

Statistical hypothesis testing compares the significance probability value and the significance level value to determine whether or not to reject the null hypothesis. This concludes "significant or not significant." However, since this process is a process of statistical hypothesis testing, the conclusion of "statistically significant or not statistically significant" is more appropriate than the conclusion of "significant or not significant." Also, in many studies, the significance level is set to 0.05 to compare with the significance probability value, p-value. If the p-value is less than 0.05, it is judged as "significant," and if the p-value is greater than 0.05, it is judged as "not significant." However, since the significance probability is a value set by the researcher according to the circumstances of each study, it does not necessarily have to be 0.05. In a statistical hypothesis test, the conclusion depends on the setting of the significance level value, so the researcher must carefully set the significance level value. In this study, the stages of statistical hypothesis testing were examined in detail, and the exact conclusions accordingly and the contents that should be considered carefully when interpreting them were mentioned with emphasis on statistical hypothesis testing and significance level. In 11 original articles published in the Journal of Lipid and Atherosclerosis in 2022, the interpretation of hypothesis testing and the contents of the described conclusions were reviewed from the perspective of statistical hypothesis testing and significance level, and the content that I would like to be supplemented was mentioned.

Comparing the long non-coding RNA expression profiles of skeletal muscle and kidney tissues from patients with diabetes

Background

Diabetes causes the dysregulation of several organs, and these effects are often closely associated with changes in the expression of long non-coding RNAs (lncRNAs), a group of non-coding RNAs, within these tissues. Previous studies have described a variety of changes in the expression profile of several lncRNAs from different organs in response to the pathogenesis of diabetes. However, none of these studies compared the expression profiles of these lncRNAs between these organs. This study was designed to identify common and specific lncRNAs involved in the progression of diabetes in the skeletal muscles and kidneys.

Methods

Publicly available RNA sequencing data of diabetic patients was obtained from the Gene Expression Omnibus database. By analyzing the expression of lncRNAs in these datasets, differentially expressed lncRNAs in each tissue between non-diabetic and diabetic patients were identified. To identify any lncRNAs changed in common in both kidney and muscle tissues, those lncRNAs that are significantly dysregulated in both datasets were selected.

Results

These evaluations identified a series of novel lncRNAs unique to each organ and several transcripts that were common to both skeletal muscle and kidney tissues in these patients. Interestingly, the genomic location of these lncRNAs suggests that they reside in close proximity to several protein-coding genes known to be related to diabetes suggesting that these lncRNAs may have a regulatory relationship with their neighboring genes.

Conclusion

These results offer valuable insights into the role of lncRNAs during the pathogenesis of diabetes.