Objective: The metrics generated from continuous glucose monitoring (CGM), such as time in range (TIR), are strongly correlated with diabetes complications. This study explored the association of perioperative CGM-derived metrics with major amputation risk in patients with diabetic foot osteomyelitis (DFO). Methods: This study recruited 55 DFO patients with grade 3–4 wounds according to the Wagner Diabetic Foot Ulcer Classification System, all of whom underwent CGM for 5 days during the perioperative period. The CGM-derived metrics were defined in accordance with the most recent international consensus recommendations. Results: Patients with major amputation had significantly less TIR and higher time below range (TBR) (all p < 0.05). In binary logistic regression analyses, a lower TIR was associated with the risk of major amputation (odds ratio: 0.83 (95% confidence interval: 0.71–0.99), p = 0.039). This association remained statistically significant after adjustments for age, sex, body mass index, type of diabetes, smoking, drinking, durations of diabetes and DFU, ankle-brachial index, albumin, estimated-glomerular filtration rate, Society for Vascular Surgery wound, ischemia, and foot infection (WIfi) stage, multidrug-resistant organisms, and hemoglobin A1c. Further adjustment for the mean amplitude of glycemic excursion (MAGE) reduced this association. TBR was also independently associated with the risk of major amputation (odds ratio: 1.60 (95% confidence interval: 1.17–2.18), p = 0.003); this association persisted after adjustment for MAGE. Conclusion: Perioperative TIR (3.9–10.0 mmol/L) and TBR (<3.9 mmol/L) were significantly associated with major amputation in hospitalized patients with DFO.

Background：Skeletal muscle is essential for glucose and lipid metabolism. Growing evidence reveals the importance of long non-coding RNAs (LncRNAs) in metabolism. This study aimed to investigate the function of LncRNA H19 (H19) in lipid metabolism of skeletal muscle and its potential mechanisms.Methods: Glucose tolerance, serum insulin and lipid content in serum and skeletal muscle were determined in control and H19-overexpressed db/db mice. Lipid metabolism was evaluated in H19-overexpressed or H19-silencing muscle cells by detecting lipid contents and mitochondria related functions. The underlying mechanisms were explored by RNA pull-down, mass spectrometry and RNA immunoprecipitation (RIP). Results: H19 was downregulated in skeletal muscle of db/db mice. H19 overexpression in db/db mice inhibited lipid ectopic deposition in skeletal muscle, meanwhile improved glucose intolerance and insulin resistance as compared with control db/db mice treated with ad-GFP. Furthermore, overexpression of H19 reversed FFA-induced lipid accumulation and increased cellular respiration in muscle cells, while H19 knockdown exhibited opposite effects in muscle cells. Mechanistically, H19 interacted with heterogeneous nuclear ribonucleoprotein (hnRNPA1) which was validated by RNA pulldown and RIP analysis, which increased translation of fatty acid oxidation closely related genes PGC1a and CPT1b. Conclusion: Our data suggest that overexpression of H19 ameliorates insulin resistance by reducing ectopic lipid accumulation in skeletal muscle. The possible underlying mechanisms are that overexpression of lncRNAH19 promotes fatty acids oxidation via targeting of hnRNPA1.

High-throughput sequencing and weighted gene co-expression network analysis (WGCNA) were used to identify susceptibility modules and genes in liver tissue for the hypoxic pulmonary arterial hypertension (PAH) animal model following intrauterine growth retardation (IUGR). A total of 5,000 genes were clustered into eight co-expression modules via WGCNA. Module blue was mostly significantly correlated with the IUGR–hypoxia group. Gene Ontology analysis showed that genes in the module blue were mainly enriched in the fatty acid metabolic process, lipid modification, and fatty acid catabolic process. The Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the genes in module blue were mainly associated with fatty acid metabolism, PPAR signaling pathway, and biosynthesis of unsaturated fatty acids. In addition, the maximal clique centrality method was used to identify the hub genes in the subnetworks, and the obtained results were verified using real-time quantitative PCR. Finally, we identified that four genes including Cyp2f4, Lipc, Acadl, and Hacl1 were significantly associated with IUGR-hypoxia. Our study identified a module and several key genes that acted as essential components in the etiology of the long-term metabolic consequences in hypoxia PAH following IUGR.