Regulating the Regulators: Mechanisms of Substrate Selection of the O-GlcNAc Cycling Enzymes OGT and OGA.

Thousands of nuclear and cytosolic proteins are modified with a single ß-N-acetylglucosamine on serine and threonine residues in mammals, a modification termed O-GlcNAc. This modification is essential for normal development and plays important roles in virtually all intracellular processes. Additionally, O-GlcNAc is involved in many disease states, including cancer, diabetes, and X-linked intellectual disability. Given the myriad of functions of the O-GlcNAc modification, it is therefore somewhat surprising that O-GlcNAc cycling is mediated by only two enzymes: the O-GlcNAc transferase (OGT), which adds O-GlcNAc, and the O-GlcNAcase (OGA), which removes it. A significant outstanding question in the O-GlcNAc field is how do only two enzymes mediate such an abundant and dynamic modification. In this review, we explore the current understanding of mechanisms for substrate selection for the O-GlcNAc cycling enzymes. These mechanisms include direct substrate interaction with specific domains of OGT or OGA, selection of interactors via partner proteins, posttranslational modification of OGT or OGA, nutrient sensing, and localization alteration. Altogether, current research paints a picture of an exquisitely regulated and complex system by which OGT and OGA select substrates. We also make recommendations for future work, toward the goal of identifying interaction mechanisms for specific substrates that may be able to be exploited for various research and medical treatment goals.

Comparison between epidural and opioid analgesia for infants undergoing major abdominal surgery.

BACKGROUND: Epidural analgesia is considered optimal for postoperative pain management after major abdominal surgery. The potential to decrease anesthetic and opioid exposure is particularly desirable for infants, given their vulnerability to respiratory depression and concern for anesthetic neurotoxicity. We reviewed our experience with infants undergoing major abdominal surgery to determine if epidural catheter use decreased anesthetic and opioid exposure and improved postoperative analgesia. METHODS: This retrospective cohort study included infants (<12 months) who underwent exploratory laparotomy, ureteral reimplantation, or bladder exstrophy repair between November 2011 and November 2014. Primary outcomes of anesthetic exposure (mean endtidal sevoflurane) and intraoperative opioid administration were compared between infants who received epidural catheters and those who did not. Secondary outcomes included postoperative pain and sedation scores and morphine equivalents administered 0-24 and 24-48 hours after surgery. RESULTS: Of 158 eligible infants, 82 were included and 47 received epidurals. Patients with epidurals underwent bladder exstrophy repair (N = 9), ureteral reimplantation (N = 8), and exploratory laparotomy (N = 30). Infants with epidurals received less intraoperative fentanyl (2.6 mcg/kg (0,4.5) vs 3.3 mcg/kg (2.4,5.8), P = 0.019) and morphine (6% (3/47) vs 26% (9/35), P = 0.014) in univariate analysis. After controlling for age and emergency surgery, differences in long-acting opioid administration persisted, with significantly less morphine given in the epidural group (OR 0.181; 95% CI 0.035-0.925; P = 0.040). Mean endtidal sevoflurane concentrations were similar between groups. There was no significant difference in postoperative median morphine equivalents. CONCLUSION: Placement of epidural catheters in infants undergoing major abdominal surgery is associated with decreased long-acting opioid requirements intraoperatively. Epidural placement does not preclude opioid exposure however, as opioids may be administered for indications other than nociceptive pain in the difficult-to-assess postoperative infant. Further prospective studies are warranted to better quantify the effect of epidural analgesia on intraoperative anesthetic exposure in infants.

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery.

Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypoxemia and provides explanations of the risk factors. The system, which was trained on minute-by-minute data from the electronic medical records of over fifty thousand surgeries, improved the performance of anaesthesiologists when providing interpretable hypoxemia risks and contributing factors. The explanations for the predictions are broadly consistent with the literature and with prior knowledge from anaesthesiologists. Our results suggest that if anaesthesiologists currently anticipate 15% of hypoxemia events, with this system's assistance they would anticipate 30% of them, a large portion of which may benefit from early intervention because they are associated with modifiable factors. The system can help improve the clinical understanding of hypoxemia risk during anaesthesia care by providing general insights into the exact changes in risk induced by certain patient or procedure characteristics.